UNIVERSITY OF GHENT

FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION

A FUTURE IN ACCOUNTING WITHOUT HUMAN INTERVENTION

Number of words: 17,117

Master’s Dissertation submitted to obtain the degree of:

Master of Science in Business Economics - Accountancy

Academic year: 2017 – 2018 Student: Mélanie Simon Student number: 01615385 Melanie.Simon@UGent.be Promotor: Prof. Dr. Patricia Everaert Patricia.Everaert@UGent.be

2

3

Title page

Title: A future in accounting without human intervention Author: Mélanie Simon E-mail address: Melanie.Simon@UGent.be Student number: 01615385 University: University of Ghent Faculty: Faculty of Economics and Business Administration Study: Master of Science in Business Economics – Accountancy Study year: 2017 – 2018 Promotor: Prof. Dr. Patricia Everaert Email address: Patricia.Everaert@UGent.be Document status: Final version Number of words: 17,117 Date: 4th of June 2018 Place: Ghent

4

Abstract Objectives:

The aim of this study is to examine the impact of automation on the accounting

profession, in order to answer the question if a future in accounting without human

intervention is possible.

Background:

In order for automation to replace the accountant, technology needs to provide useful

financial information; it needs to be relevant, represented faithfully, comparable,

verifiable, timely and understandable.

Systematic literature study:

32 articles were selected, main subjects identified were: consequences on accounting,

moral decision-making, future role, implications on small accounting firms, implications

on the labour market and solutions.

Methods:

Semi-structured interviews were conducted with accountants from eight different

companies in Belgium and Luxembourg. Professionals have been interviewed regarding

their use of technology and their future perspective on the accounting profession.

Results:

Eight interviews have been conducted, main subjects identified were: the use of

automation, qualitative characteristics, skills and implication on small accounting firms.

Results show that the accountant will be using automation for routine tasks, rather than

being replaced by it. Tasks that require critical-thinking and creativity seem to be more

difficult to be automated. In the coming years, the technology will be able to assist

accountants in non-repetitive tasks. The business model of accounting firms will change

and accountants who are not ready for automation will be at risk of being replaced by

automation. Specific skills will already need to be acquired before starting to work.

Relevance for practice:

Accountants will shift to either advisory or consultancy. IT-, tax- and analytical skills will

have to be developed. Universities will need to change their education programs in order

for future accountants to be ready to work alongside automation.

5

Table of content

Introduction 9 1.1 Context 9 1.2 Problem Statement 9 1.3 Research question 10 1.4 Structure of the thesis 10 2. Artificial Intelligence and automation 11 3. The Accountant, Auditor and Management Accountant 13 3.1 Definitions 13 3.2 A brief history of the accountant 14 3.3 Financial reporting 15 3.3.1 Objectives of the financial reporting 15 3.3.2 Qualitative characteristics of useful financial information 16 3.3.2.1 Fundamental qualitative characteristics 16 3.3.2.2 Enhancing qualitative characteristics 17

4. Systematic literature study 19 4.1 Databases and search strategy 19 4.2 Study selection 19

4.3 Quality appraisal 18 4.4 Data extraction 24 4.5 Description of the studies 24 4.6 Consequences on the accounting profession 25 4.7 Moral decision-making 30 4.8 Future role 30 4.9 Implications on small accounting firms 32 4.10 Implication on the labour market 32 4.11 Solutions 33

5. Methodology 35 5.1 Research design 35 5.1.1 Interviews 35 5.1.2 Population 35 5.1.3 Place 35 5.1.4 Description of the respondents 36 5.2 Data collection 37 5.2.1 Semi-structured interviews 37 5.3 Reliability and validity 37 5.3.1 Reliability 38 5.3.2 Validity 38 5.3.2.1 Internal validity 38 5.3.2.2 External validity 39 5.4 Ethical considerations 39

6

6. Results 41 6.1 Description of the results 41 6.2 The use of automation in the company 41 6.3 Qualitative characteristics of the financial information 47 6.4 Skills 51 6.5 Small accounting companies 57 7. Discussion 59 8. Conclusion 61 9. Limitations 63 10. Future research 65

11. Management and policy implementations 67

References 69 Annexes 77 Annex 1: Printscreen databases 78 a. ABI/INFORM Collection 78 b. Accounting, Tax and Banking Collection 78 c. Web of Science 79 Annex 2: Overview selected articles 80 Annex 3: Interview guideline 89

Annex 4: Confidentiality agreement 89

7

Acknowledgments The completion of this thesis has been very fascinating and instructive, but also hard

work. These seven months of work have been very challenging for me and I would

like to thank the people who contributed directly or indirectly to the completion of the

work presented in this thesis.

This accomplishment would not have been possible without them.

I would first like to thank my promoter, Prof. Dr. Patricia Everaert. The door to her

office was always open whenever I had questions about my research. I thank her for

advising and guiding me to the right direction during these last couples of months.

I would like to express my gratitude to all the respondents of the interviews for taking

time to participate in this study.

My sincere gratitude also goes out to Inge van der Veen and to Casper van den Berg

for carefully and critically reviewing my thesis.

I would especially like to express my gratitude to my partner for providing me moral

and intellectual support throughout the process of researching and writing this

dissertation. Without him I would not have come this far.

8

List of abbreviations AI Artificial Intelligence

BDO Binder Dijker Otte

CEO Chief Executive Officer

CFO Chief Financial Officer

CO Controlling

FI Financial Accounting

GDPR General Data Protection Regulation

IASB International Accounting Standards Board

IBM International Business Machines

IFRS International Financial Reporting Standards

IT Information Technology

KPI Key Performance Indicator

KPMG Klynveld Peat Marwick Goerdeler

LPL Lo Presti Ludovic

PS Project System

9

Introduction The first chapter describes the context and the problem statement. Then, the research

question will be presented and the structure of the thesis will be described.

1.1 Context

In today’s modern world, a lot of technologic advances have been developed at an

undoubtedly fast rhythm, amplifying the need for companies to invest in Artificial

Intelligence (AI) and automation.

At Google's annual Input/Output developer conference, Google affirmed its desire to

integrate Artificial Intelligence into people’s daily life through a smart personal assistant

(Staff, 2017). Other technology giants as Apple, Facebook, Microsoft and Amazon are

also interested in AI and invest heavily in this technology. The use of Artificial Intelligence

and automation can reduce the need for human labour. This leads to uncertainty

concerning certain professions, such as accounting (Manjoo, 2017).

According to a study conducted by Frey & Osborne (2017), 702 job titles are at risk of

automation. Among these professions, accounting is on top of the list with 94 percent

probability of being computerized in the next two decades (Nagarajah, 2016). Artificial

Intelligence can be integrated into accounting processes and thereby replace humans. In

fact, an artificial agent called Amelia has already started at Shell and Baker Hughes (two

of the biggest gas groups) to take over the duties of accountants and call centre agents.

The system has the ability to understand natural language that allows to interact with

humans. It does not only recognize words, it also understands the meaning of them.

These are tangible signs that the employment of white-collar workers could be

threatened by the rise of Artificial Intelligence (Twentyman, 2017).

Recently, International Business Machines (IBM)'s AI has demonstrated its exceptional

ability to replace humans in performing tasks previously reserved for human intelligence.

The software can answer any question asked by a human in natural language, orally or

in writing, in eight different languages (Tual, 2017).

1.2 Problem Statement

According to an analysis provided by Accenture, 40 percent of transactional accounting

work could be automated by 2020 (Seek, 2017). As an authority on the profession, the

Association of Chartered Certified Accountants is sceptical about the future of the

accountants. The skills that accountants nowadays apply may not be relevant anymore

in the next coming years (Galarza, 2017).

10

The aim of this study is to research the impact of automation in the accounting field. In

order for automation to be able to replace accountants, useful financial information still

has to be provided. Therefor, the attributes that make financial information useful also

have been researched.

1.3 Research question

The following research question is formulated: is a future in accounting without human

intervention possible?

In order to answer this research question, a systematic literature review and interviews

have been conducted. First, all the literature regarding the impact of technology on the

accounting profession has been gathered. Later, several interviews have been

conducted with eight different Belgian and Luxembourgish companies.

1.4 Structure of the thesis

This thesis consists of eleven chapters. The first chapter is the introduction in which the

context, the problem statement and the research question is described. The second

chapter consists of background information regarding Artificial Intelligence and

automation. The third chapter consists of definitions of the accountant, the auditor and

the management accountant. The qualitative characteristics will also be addressed in this

chapter. The systematic literature review can be found in chapter four including the

search strategy and the results. The methodology of the empirical study can be found in

chapter five, where the study design, the data collection and the reliability and validity.

The sixth chapter consists of the results from the semi-structured interviews. The

discussion can be found in chapter seven, in chapter eight the conclusion and in chapter

nine the limitations. Suggestions for future research are described in chapter ten. Finally

in chapter eleven, the management and policy implications of this study are given.

11

2. Artificial Intelligence and automation In order to answer the question if a future in the accounting profession without human

intervention is possible, in this chapter background information about the subject will be

provided. Four things are mainly important: 1) what is Artificial Intelligence and

automation 2) definitions of the accountant, the auditor and the management accountant

3) a brief history of the accounting profession and 4) objectives of the financial reporting

and when automation is useful in light of the accounting profession.

Artificial Intelligence is the theory and development of computer systems that are able to

perform tasks that normally require human intelligence, such as visual perception,

speech recognition, decision-making and translation between languages (Oxford

Dictionary, n.d.a). The system can perform functions that a human brain does, like

learning and problem solving.

The term Artificial Intelligence was first introduced in 1956 by John McCarthy (Smith,

McGuire, Huang et al., 2006), but in 1950 Alan Turing already wrote a paper about the

ability of machines to do intelligent things. The purpose of Turing’s paper was to consider

the question “if machines can think”? He replaced this question by testing if a machine

could replace a human being in the game of imitation. The purpose of the test was to ask

a person to make the distinction between answers given by a machine and those

provided by a human, by communicating via an old teleprinter. Turing predicted that in

the year 2000, the machine would be able to fool 30% of the respondents in a five-

minute test.

Familiar definitions are automation, big data, machine learning and Expert Systems.

Automation is “the technique, method or system of operating or controlling a process by

automating devices, reducing human intervention to a minimum. Automation has a single

purpose: to let machines perform repetitive, monotonous tasks” (Dictionary, n.d.).

“Automation is a technology that actively selects data, transforms information, makes

decisions and controls processes” (Lee & See, 2014).

Big Data is “a set of extremely large data that may be analysed computationally to reveal

patterns, trends and associations, especially relating to human behaviour and

interactions. The more data the machine collects, the more it will be able to learn and the

better it will function” (Oxford Dictionary, n.d.b). “Big Data has the ability to scan large

volumes of data and perform analytics with sophisticated algorithms to facilitate decision-

making in the accounting function” (Brands & Smith, 2016).

12

Machine learning is “the ability of a computer to learn from experience, for instance to

modify its processing on the basis of newly acquired information. It is a type of AI that

focuses on the development of computer programs that can access data and use it to

learn for themselves” (Oxford Dictionary, n.d.c). According to Tynan (2017), “machine

learning systems essentially code themselves, developing their own instructions by

generalizing from examples. The classic example is image recognition, where the

machine learning will identify what is on the image without a human ever telling the

machine what is on the picture.”

Expert system is “a computer system that can provide information and expert advice on a

particular subject. The program asks users a series of questions about their problem and

gives them advice based on its store of knowledge” (Oxford Learner’s Dictionary, n.d.).

Quinn (1990) defined Expert System, as “an interactive computer program that asks the

same questions a human expert would ask, and from the information given to it by the

user, provides the same answer the expert would provide. If a body of knowledge can be

codified into a set of questions and answers, it can be incorporated into an Expert

System software program.”

13

3. The Accountant, Auditor and Management Accountant The field of accounting involves the study of accountancy, auditing, finance, financial

management and tax (Wohlner, n.d.). This thesis will only focus on the accountant, the

auditor and the management accountant. In this chapter, these definitions are given, as

well as a brief history of the accountant. Finally, the financial reporting will be addressed.

3.1 Definitions

The accountant

An accountant is a qualified person who is trained in bookkeeping and in preparation,

auditing and analysis of accounts. Accountants prepare annual reports and financial

statements for planning and decision-making and advise on tax laws and investment

opportunities (Business Dictionary, n.d.). Accounting is the process of measuring and

summarizing business activities, interpreting financial information and communicating the

results to management and other decision makers (Minnesota Libraries, n.d.).

The auditor

When the accounting process ends, auditing begins.

Auditing is the purpose of determining the true and fair representation of the financial

statements. The auditor examines the financial report of an organization.

There are four main steps in the audit process (PriceWaterhouseCoopers, n.d.). The first

step is to determine the auditor’s role and the terms of engagement, which is a letter

signed by the client. The second step is to plan the audit, which includes details of

deadlines and the departments the auditor covers. Once the auditor is aware of the

company's sector and its internal control and has identified the risks, it is necessary to

analyse the accounts more precisely in order to identify the risks of any fraud or errors.

This is the third step. The last and most important element of an audit is reporting the

results. The results are documented in the report of the auditor, including the justification

of the auditor’s opinion. This opinion is the conclusion of all the work carried out during

the audit.

14

The management accountant

The management accountant is a professional who assists managers by helping them

making decisions. The management account hence prepares and analyses the financial

statements of a company and analyse its financial performance in order to advice the

managers in the decisions-making process (Institute of Management Accountants,

2008). The management accountant provides the necessary information and advices to

the decision-makers. To forecast the future and to monitor the performance of the

company, managers will need information provided by the management accountants

(Certified Practising Accountant Australia, 2012).

3.2 A brief history of the accountant

The accounting profession has recently been recognized, but the art of accounting is

nearly 6,000 years old (Mason, 1953). The Romans and Egyptians were the first to use

accounting in commercial life. In the Roman Empire, one of the purposes of accounting

was to present the economic situation of the merchants to their customers. The purpose

was to record on the left side of the notebook the use or consumption of resources, while

the right part was used for the origin or production of resources (Alexander, 2002).

Although accounting has indeed been used since the Stone Age, the most significant

development with regards to modern accounting occurred during the Renaissance period

in Italy. Brother Luca Bartolomes Pacioli, an Italian born in 1445, is the inventor of

modern accounting. Pacioli was the first person to publish a work on double-entry

bookkeeping system (Mason, 1953).

The main principles of accounting that are currently used in companies were found at

that time. Modern accounting techniques are based on double entry bookkeeping,

defined as “debit” and “credit”. Three books were necessary to keep adequate records

for every business: a ledger, a journal and a memorandum book. A trial balance has to

be made at the end of each year (Mason, 1953).

Nowadays there are standards set by the International Accounting Standards Boards

(IASB) to guide and harmonize the accounting practices. The IASB develops and

approves International Financial Reporting Standards (IFRS), a set of international

accounting standards to specify how to report the accounts, so that everybody can

understand the business and the reporting from companies situated in different

countries. The Board regularly updates the Conceptual Framework for Financial

15

Reporting to facilitate the use of IFRS Standards. The Conceptual Framework includes

qualitative characteristics of the financial information to help accountants decide what

information to provide and how to present it.

In the next subchapter, the objectives of the financial reporting and the qualitative

characteristics will be described. In accounting, automation is useful when it is able to

perform the same tasks as accountants do. In other words: AI needs to provide useful

financial information. Useful financial information, as described by the Conceptual

Framework (Ernst & Young, 2010), will be explained.

3.3 Financial reporting

The conceptual framework for financial reporting sets out the concepts for the

preparation of the financial statements for external users. The conceptual framework is

structured according to the following hierarchy:

- The objectives of the financial reporting are stated;

- The qualitative characteristics of the information contained in the financial

statements;

- The definition, recognition and measurement of the elements from which financial

statements are constructed (assets, liabilities, equity, income and expenses).

The following chapter explains the objectives of the financial reporting and the qualitative

characteristics of useful financial information (Deloitte, n.d.).

3.3.1 Objectives of the financial reporting

The purpose of financial reporting is to provide useful financial information about an

entity to potential investors, lenders and other creditors who use that information to make

decisions about buying, selling or holding equity or debt instruments and providing or

settling loans or other forms of credit (IFRS, n.d.).

To achieve this objective, the financial reports must provide information on the economic

resources of the entity, their counterparty and the transactions and other events and

circumstances that affect them. The degree of usefulness of financial information

depends on the qualitative characteristics.

16

3.3.2 Qualitative characteristics of useful financial information

The qualitative characteristics of financial information, as set out in the Conceptual

Framework of the IASB are fundamental to identify the types of information that are most

likely to be useful for the purpose of making decisions about the reporting entity based

on the information presented in its financial report (Ernst & Young, 2010).

The revised Framework distinguishes two types of qualitative characteristics that are

necessary to provide useful financial information: fundamental qualitative characteristics

and enhanced qualitative characteristics.

3.3.2.1 Fundamental qualitative characteristics

By fundamental qualitative characteristics is meant: the relevance and the faithful

representation of financial information.

Relevant information is capable of influencing the decision made by users. It is capable

of making different decisions if it has predictive value, confirmatory value or both.

Predictive value helps users in predicting or anticipating future outcomes. Confirmatory

value enables users to check and confirm earlier predictions or evaluations.

The Financial reports represent economic phenomena in words and numbers. To give a

perfectly faithful picture, the financial information must have three characteristics: it must

be complete, neutral and free of errors. The revised Framework acknowledges limitations

in achieving a faithful representation; financial information might not be totally free from

errors. However, a faithful representation is achieved if no errors or omissions affect the

description of economic phenomena and the process applied to produce reported

information has been selected and applied without errors.

17

3.3.2.2 Enhancing qualitative characteristics

The usefulness of financial information is enhanced when it is comparable, verifiable,

timely and understandable. The purpose is to enhance the relevant and faithfully

financial information.

Comparable:

User decision-making implies making choices between various options, such as selling

or holding an investment or investing in one entity over another. Therefore, information is

more useful if it can be compared with other items, in different periods within a set of

financial statements and across different reporting entities.

Verifiable:

Verifiability assumes that different well-informed and independent observers could come

to a consensus -but not necessarily to a complete agreement- on whether a particular

depiction of an event or transaction is a faithful representation.

Timely:

Timeliness of financial information involves the need to make the information available in

time to decision-makers, in order to influence their decisions. The information should not

be significantly delayed; otherwise it will be of little or no value. However, some

information may also continue to be useful after the end of a reporting date because, for

example, some users may need to identify and evaluate trends.

Understandable:

The information is understandable when it is classified, characterized and presented in a

clear and concise manner. A company's financial information should be presented in

such a way that a person with a reasonable knowledge of business and finance, and the

willingness to study the information, should be able to comprehend it.

18

19

4. Systematic literature study The fourth chapter discusses the methodology of the literature study and the obtained

results from the systematic literature study.

4.1 Databases and search strategy

The databases that were searched for relevant studies are: ABI/INFORM Collection,

Accounting, Tax and Banking Collection and Web of Science. The searches were

conducted in January 2018 (Week 2). The following search strategy was used:

(accountancy OR audit OR accounting OR auditing) AND (automation OR technology

OR artificial intelligence OR robots) AND (Future)

In the database ABI/INFORM, this search strategy resulted in 764,477 articles, in

Accounting, Tax and Banking Collection it resulted in 81,490 articles and finally in Web of

Science it resulted in 5,695 articles. Due to the number of articles found in ABI/INFORM

Collection and Accounting and Tax and Banking Collection, the following filters were

used: full-text, peer reviewed, scholarly journals and articles. These filters led to 75,236

articles in ABI/INFORM and 7,159 articles in Accounting, Tax and Banking Collection. No

filters were used in the database Web of Science. The total number of articles found by

this searching strategy was 88,090. In annex 1, a screenshot of all databases can be

found.

4.2 Study selection

One reviewer searched for relevant studies using the search strategy described above.

The selection of studies was determined by two steps: the studies were first filtered on

relevance of the title (n=164) and after that, the studies were filtered on relevance of the

abstract (n=92). Duplicates and studies written in another language than English were

excluded (n=44). The remaining studies (n=48) were read full-text and articles not related

to the different technologies as described in Chapter 2 and not related to the future of

accounting were excluded. The 32 selected articles underwent quality appraisal.

The flow chart of the selection process can be found on the next page.

20

Figure 1: Flow chart of the selection process

4.3 Quality appraisal

The quality assessment of the selected articles was conducted by using Hawker, Payne,

Kerr (et al., 2002)’s framework. This framework includes nine questions, regarding the

following domains: abstract and title, introduction and aims, method and data, sampling,

data analysis, ethics and bias, results, generalizability and implications and usefulness.

Each of the domains can be scored from 1 (very poor) to 4 (good), with a maximum

score of 36. High quality is defined as 30-36 points and medium quality as 24-29 points.

Of the 32 articles, 13 articles had a high-quality score and 13 articles had a medium

quality score. 6 articles had a lower quality score, but the findings were yet seen as

interesting for this research.

The framework for quality appraisal can be found in table 1, in table 2 to 5 the quality

assessment of the selected articles can be found.

21

1. Abstract and title Did they provide a clear description of the study?

2. Introduction and aims Was there a good background and clear statement of the aims?

3. Method and data Is the method appropriate and clearly explained?

4. Sampling Was the sampling strategy appropriate to address the aims?

5. Data analysis Was the description of the data analysis sufficiently rigorous?

6. Ethics and bias Have ethical issues been addressed, and what has necessary ethical approval gained? Has the relationship between researchers and respondents been adequately considered?

7. Results Is there a clear statement of the findings?

8. Generalizability Are the findings of this study transferable to a wider population?

9. Implications and usefulness How important are these findings to policy and practice?

Table 1: Framework for Quality Appraisal

22

Al-Htaybat et al., 2017

Anonymous, 1987

Arntz et al., 2017

Baldwin et al., 2006

Beaman et al., 2007

Blum, 1966

Chase et al., 1991

Chelliah, 2017

Cole et al., 1992

1. Abstract and title 4 2 4 4 4 2 4 3 2

2. Introduction and aims 4 2 4 3 3 2 3 3 2

3. Method and data 4 2 4 3 4 2 2 2 2

4. Sampling 4 2 4 3 4 2 2 2 2

5. Data analysis 4 2 4 3 4 3 2 2 3

6. Ethics and bias 4 2 3 3 4 2 2 2 2

7. Results 4 3 3 2 3 3 3 3 3

8. Generalizability 4 3 4 3 4 3 3 3 3

9. Implications and usefulness 4 3 4 2 3 3 3 3 3

Total 36 21 34 26 33 22 24 23 22

Table 2: Framework for Quality Appraisal

Coyne et al., 2017

David, 2015

Frey et al., 2013

Gamage, 2016

Gonzalez et al., 2012

Henry et al., 2015

Herbert et al., 2016

Kim et al., 2017

1. Abstract and title 2 3 4 3 4 3 2 3

2. Introduction and aims 2 2 4 2 4 3 3 3

3. Method and data 2 3 3 3 4 2 3 4

4. Sampling 2 3 4 3 4 2 3 4

5. Data analysis 3 3 4 3 3 2 3 4

6. Ethics and bias 2 3 3 3 3 3 3 4

7. Results 3 3 4 3 4 3 3 4

8. Generalizability 3 3 4 3 3 3 3 4

9. Implications and usefulness 3 3 3 3 3 3 3 4

Total 22 26 33 26 32 24 26 34

Table 3: Framework for Quality Appraisal

23

Kokina et al., 2017

Liu et al.,

2014

Marcello et al., 2017

Moudud-Ul-Huq, 2014

Omar, 1993

Oschinski et al., 2017

Özdoğan, 2017

Parham et al., 2012

1. Abstract and title 3 2 2 3 4 4 3 3

2. Introduction and aims 3 3 2 4 4 4 3 2

3. Method and data 4 3 4 4 2 3 3 3

4. Sampling 3 3 4 4 3 3 3 3

5. Data analysis 3 3 3 3 3 4 3 3

6. Ethics and bias 4 3 2 3 3 4 3 3

7. Results 3 3 2 3 4 4 3 3

8. Generalizability 2 3 3 3 3 3 2 3

9. Implications and usefulness 2 3 3 3 4 4 3 3

Total 27 26 25 30 30 30 26 26

Table 4: Framework for Quality Appraisal

Rattunde

et al., 2016

Sangster, 1994

Silverman, 1966

Sorgner, 2017

Tuzhilin, 2004

Wilson et al., 1992

Zarowin, 1994

1. Abstract and title 3 3 3 4 3 3 3

2. Introduction and aims 3 4 3 4 4 3 3

3. Method and data 3 4 3 4 2 4 2

4. Sampling 3 4 3 4 2 4 2

5. Data analysis 4 4 3 4 2 4 3

6. Ethics and bias 4 4 3 3 2 3 3

7. Results 4 4 3 4 3 4 3

8. Generalizability 4 3 3 4 2 3 3

9. Implications and usefulness 4 3 3 4 3 3 3

Total 32 33 27 35 23 31 25

Table 5: Framework for Quality Appraisal

24

4.4 Data extraction

From the included articles, the data was gathered using a standard data extraction form:

author, title, year, country, study objective, method and findings. The data of the articles

used can be found in annex 2.

4.5 Description of the studies

The included studies vary in method of study, location of study and time of study.

Regarding the study methods, the 32 studies that are included can be categorized in

sixteen review studies (Kokina & Davenport, 2017, Oschinski & Wyonch, 2017, Chelliah,

2017, David, 2017, Coyne, Coyne & Walker, 2017, Rattunde, 2016, Gamage, 2016,

Henry & Hicks, 2015, Liu & Vasarhelyi, 2014, Moudud-Ul-Huq, 2014, Baldwin, Brown &

Trinkle, 2006, Silverman, 1996, Omar, 1993, Chase & Shim, 1991, Anonymous, 1987 &

Blum, 1986), eight survey studies (Özdoğan, 2017, Sorgner, 2017, Gonzalez, Sharma &

Galetta, 2012, Parham, Noland & Kelly, 2012, Beaman & Richardson, 2007, Sangster,

1994, Tuzhilin, 2004 & Wilson & Sangster, 1992), four interview studies (Al-Htaybat &

Von Alberti-Alhtaybat, 2017, Marcello, Ray, Carmichael et al., 2017, Herbert, Dhayalan &

Scott, 2016 & Zarowin, 1994), three quantitative studies (Kim, Kim & Lee, 2017, Arntz,

Gregory & Zierahn, 2017 & Frey & Osborne, 2013) and one case study (Cole & Hales,

1992).

Of the 32 studies, 19 were conducted in the United States (Coyne et al., 2017, Kokina et

al., 2017, David, 2017, Marcello et al., 2017, Rattunde, 2016, Henry et al., 2015, Liu et

al., 2014, Frey et al., 2013, Parham et al., 2012, Gonzalez et al., 2012, Beaman et al.,

2007, Baldwin et al., 2006, Tuzhilin, 2004, Silverman, 1996, Zarowin, 1994, Cole et al.,

1992, Chase et al., 1991, Anonymous, 1987 & Blum, 1986), seven were conducted in the

United Kingdom (Al-Htaybat et al., 2017, Kim et al., 2017, Özdoğan, 2017, Chelliah,

2017, Herbert et al., 2016, Sangster, 1994 & Wilson et al., 1992), two in the Netherlands

(Arntz et al., 2017 & Omar, 1993), one in Canada (Oschinski et al., 2017), one in India

(Moudud-Ul-Huq, 2014), one in Australia (Gamage, 2016) and one in Russia (Sorgner,

2017).

The year the studies took place varies from 1986 to 2017. Ten studies took place in 2017

(Coyne et al., Sorgner, Al-Htaybat et al., Marcello et al., Kokina et al., Kim et al., Arntz et

al., Özdoğan, Oschinski et al. & Chelliah), three studies in 2016 (Gamage, et al.,

Dhayalan & Scott), two studies in 2015 (David & Henry et al.), one study in 2014

(Moudud-Ul-Huq), one study in 2013 (Frey et al.), one study in 2014 (Liu et al.), two

studies in 2012 (Parham et al., & Gonzalez et al.), one in study 2006 (Baldwin et al.), one

25

study in 2007 (Beaman et al.), one study in 2004 (Tuzhilin), one study in 1996

(Silverman), two studies in 1994 (Sangster, Zarowin), one study in 1993 (Omar), two

studies in 1992 (Cole et al. & Wilson et al.) one study in 1991 (Chase et al.), one study in

1987 (Anonymous) and one study in 1986 (Blum).

Main subjects identified were: 1) consequences on the accounting profession, 2) moral

decision-making, 3) future role, 4) implication on small accounting firms, 5) implications

on the labour market and 6) solutions. Each of these topics will be discussed in the next

paragraph.

4.6 Consequences on the accounting profession

The first step is to distinguish routine tasks (which can easily be automated) and non-

routine tasks (which are more difficult to be performed by machines or software). Jobs

that require critical thinking and human contact will not be automated soon (Oschinski et

al., 2017). These occupations need high-level creativity and training. Jobs that generally

consist of routine tasks do not require a level of high education and only little human

interaction is needed compared to non-routine tasks. Non-routine tasks can be divided

into manual occupations and intellectual occupations. Manual occupations generally

require lower qualifications than cognitive jobs that generally require a high level of

education (Oschinski et al., 2017).

Herbert et al. (2016) explored the possibilities for transforming the way professional work

in the future, by using automation. The study describes that since automation is used to

eliminate routine and repetitive tasks, it will allow employees to focus on more creative,

non-structured tasks that require more thinking. While focusing more on creative, non-

structured tasks, the value of the accountant`s contributions will increase. Kim et al.

(2017) examined the relative quantities of jobs that are susceptible to become

computerized in the future and concluded that jobs that require little creativity or complex

training (routine occupations), are most likely to be replaced. Jobs that require critical

thinking and human contact will not be easily automated. These occupations require

high-level creativity and training. Tuzhilin (2004) found the same results by examining

current trends in the technology-driven automation and the effect that it will have on

different jobs. The author describes that repetitiveness, stability and structure are the

characteristics of jobs that can be automated. In other words: routine production jobs can

be performed by automation. Arntz et al., (2017) demonstrated that empirical

26

assessments are wrong saying that half of all jobs in western industrialized countries are

at risk of automation in the next 10 to 20 years. According to the authors, many

accounting tasks are already automated in firms, such as invoicing, payroll and book-

keeping, which involve the processing of large amounts of data and consists of repeated,

stabile and structured tasks. In general, the process of accounting information has

already become largely automated. According to Liu et al. (2014), automation will

constantly develop and make some tasks -like bookkeeping- disappear and at the same

time create new ones.

Wilson et al. (1992) examined the use of computer technology by the UK accounting

profession and why the accounting profession should be aware of automation. By

conducting a survey under the population of members of the Institute of Chartered

Accountants of Scotland, the authors asked the respondents to determine which factor

could be a motivation for technological change. The majority identified the need to meet

accounting deadlines as the most significant motivation, just as the importance to provide

better information to clients. According to Al-Htaybat et al. (2017), by using technology

the quality and relevance of the accounting information will improve. Big Data reduces

the time of reporting, since technology can provide real-time updates. The computerized

accounting systems are able to convert accounting data into valuable information, which

reduces work-time and improves the quality of the financial information. Companies are

looking for efficiency as well as productivity and profitability. As a consequence,

companies will prefer using technology rather than human intervention (Wilson et al.,

1992). According to Anonymous (1987) the benefit of using an Expert System is that the

system will not leave the company or retire unlike employees. Cole et al. (1992)

published an article describing the benefits of automation. According to the authors,

automation might eliminate some tasks and by reducing the number of employees the

labour costs of the company will decrease. The system could be useful in situations

where a human intervention is costly or in situations where a human expert is not

available. Problems, which were solved only by the people with a specific expertise, can

now be solved by the system and enables the firm to enter a new market (Anonymous,

1987). Furthermore, Expert Systems can train new inexperienced accountants, who

otherwise needed intervention from an employee of the company. The employee

productivity can hence improve by keeping the experienced personnel working on

important tasks and by giving the new accountants enough training to become effective.

Gonzalez et al. (2012) were interested in the general adoption of the technology and

27

explained that, due to the pressure coming mainly from clients and competition,

companies need to invest in automation. To become more efficient, companies need to

satisfy their clients’ expectation regarding the decrease in prices. By automating the

processes of certain tasks, companies become more efficient and therefor stay ahead of

the competition.

The study of Gamage (2016) explored the latest developments in Big Data and its impact

on accounting education. According to these findings, the decision-aid is one of the

greatest benefits of Big Data. Accountant researchers have already been using

automation for the decision-making process. The measurement of the data has been

enhanced and the information is better understood (Liu et al., 2014). Expert Systems

have the benefit that it can assist the accountant during the analysis of complex data.

The systems can provide help to professionals to make sure that the right questions are

addressed, and the right decisions are being made (Anonymous, 1987). The system can

help to identify plausible issues and guide the accountant to find the best solution to

those problems (Anonymous, 1987). Data accessibility has been enhanced by

technologic innovation, such as the financial information provided to accountants

increased in effectiveness and efficiency (Liu et al., 2014). Hence, the decision-making

process will be improved by providing more accurate and detailed data (Al-Htaybat et al.,

2017).

According to Herbert et al. (2016), 90 percent of the errors or accidents are caused by

humans. Machine learning would be a solution to reduce these errors. In the coming

years, 40 percent of the companies will use automation to avoid those human errors.

According to Anonymous (1987), due to the fast improvement in technology, Expert

Systems are likely to become part of some accounting tasks, for instance:

- Account attribute analysis. The Expert System provides guidance concerning different

accounts;

- Quality review. Expert Systems are able to improve the quality of accounting such as in

compliance and annual report disclosures, by fulfilling or judging the quality review of the

firm;

- Accounting decisions. The treatment of complicated transactions can be facilitated with

the use of Expert Systems, which are able to help accountants in making decisions;

- Tax planning. Experts Systems are able to make complicated analyses and provide the

appropriate documents to accountants;

28

- Management consulting. Management consulting is another area where Expert

Systems are introduced to identify patterns and relationships. The system will provide

solutions based on the situation and evaluate the effect of changes in consulting

engagements.

Auditors are also able to take advantage of automation. Baldwin et al. (2006) reviewed

the nature of accounting and auditing problems and the need for the application of

automation. According to this study, auditing is a field that is intrigued by the use of

automation. Auditors have to deal with uncertainties and incomplete financial information,

but the decisions that are being made are often repetitive. Chase et al. (1991) studied

the use of Expert Systems in large accounting firms. Firms generally use Expert Systems

mostly to reduce time and costs while auditors have more time to take important audit

decisions. Expert Systems bring more accuracy and consistency in the audit procedures

and auditors can work faster without having to ask questions to a senior auditor

(Moudud-Ul-Huq, 2014).

A study from Moudud-Ul-Huq (2014) showed that automation was not suitable for every

audit task. The audit tasks in which, according to this study, automation is useful to help

the auditor during the decisions-making process are:

- Audit planning. Expert Systems are able to help evaluating risks, establishing audit

objectives and giving prescription regarding the audit steps and procedures. The Expert

System not only increases reliance on the decision aids, it also enhances the decision

during the audit planning.

- Analytical review procedures. The use of artificial neural network improves the

analytical review procedures because the system provides objective information about a

client company.

- Materiality assessment. The Expert Systems are able to identify plausible

misstatements in the financial statements.

- Materiality judgments. The Expert Systems can be used during the materiality

judgements to assist the auditor during the formulation of judgements.

- Internal control evaluation. The Expert Systems are able to increase effectiveness and

efficiency during the evaluation of the internal controls. Accounting firms could benefit

from the use of to discern potential weaknesses.

29

- Risk assessment. The Expert Systems alerts the auditor when audit tests are

unnecessary to perform on firms free of misstatement. This should improve the efficiency

as well as effectiveness of the audit. The Expert Systems is able to provide several

benefits during the risk assessment procedure including: advisory, consistency of the

decisions and increase in productivity.

- Going-concern decisions. The Expert system assists and supports auditor’s judgment

about a client’s going concern. Advices from an auditor specialist are not needed

anymore, which represents a cost advantage for the companies.

Nevertheless, relying only on the data provided by technology and not using the

experience and knowledge of accountants could be dangerous. Accountants are sceptic

regarding the reliability of the financial information provided by automation (Al-Htaybat et

al., 2017). The lack of sufficient knowledge of Big Data and the analysis of the data could

generate inappropriate results, accountants may not be able to analyse and interpret the

results correctly. Marcello et al. (2017) held a roundtable discussion on the past, present,

and future of the auditing profession. One of the professionals from the roundtable

discussion believes that accountants and auditors need to be careful when using Artificial

Intelligence. According to this respondent, human intelligence exceeds machine learning.

The professional is sceptical about the use of Artificial Intelligence and does not trust

machine learning concerning the decision-making. The paper of Sangster (1994)

considered the way in which organisations develop. The results show that 60 percent of

the respondents would not use the Expert System in the most effective manner and 67

percent of the respondents indicated that this type of technology would not be trusted.

Frey et al. (2013) examined how susceptible jobs can be computerized. This study

indicates that the current technology is not yet sufficiently developed to perform tasks

that require human thinking. In the future, some non-routine manual tasks will probably

be performed by automation. The technology evolves so fast that the machine learning is

nowadays in a position to replace many of the decisions that a human used to make.

30

4.7 Moral decision-making

According to Omar (1993), Artificial Intelligence needs to possess four attributes to be

able to make a valid moral judgment:

1) Knowledge of all relevant facts;

2) In-biasedness;

3) Freedom from disturbing passion;

4) The ability to vividly imagine the feelings and circumstances of the parties

involved.

According to this study, Artificial Intelligence is able to perform the three first conditions.

However, the last condition involves emotions, which AI is not able to fulfil. Furthermore,

the machine does not know what happened in the past, neither what is happening in the

present nor what will happen in the future.

Zarowin (1994) examined the computer revolution in the accounting profession by

interviewing the Chief Executive Officer (CEO) of the Computer Associates International.

The respondent recognized that until now, Artificial Intelligence could not perform

accountants’ most valuable functions: interpreting and analysing financial information.

Accountants do not need to worry about being replaced by technology yet. Kokina et al.,

(2017) discussed the current capabilities of cognitive technologies and the implications

these technologies will have on human auditors and the audit process. According to an

interview conducted during this study, senior accountants in large firms stated that the

need for human accountants would not go away anytime soon. At least over the next

couple of years, accounting is one of the many business fields that are likely to be

augmented by technology, rather than fully automated.

4.8 Future role

Beaman (et al., 2007) studied the role of the management accountants in the future and

state that the accountant’s role is dominated by scorekeeping and other requirements.

Accountants need to develop their skills regarding the use of AI if the employees want to

keep adding value to the firm. The authors concluded that management accountants who

continue spending much time in scorekeeping activities (instead of providing decision

support services to managers), risk losing their jobs. Management accountants need to

know what the critical pieces and the outcomes of data are, in order to add value to the

business (Gamage, 2016).

31

Young accountants coming into the profession need to understand what are the skills

needed to work alongside automation. The need to acquire and develop these skills is

crucial to avoid job loss. Many of the jobs that will persist in the future will require

interpersonal interaction, flexibility, adaptability and problem solving (David, 2015).

Future accountants will be required to have diversity of experience, curiosity and the

ability to learn continuously. The profession does not only need students who understand

audit standards, the students also need to know how to solve problems and how to think

critically (Marcello et al., 2017).

Parham et al. (2012) examined which skills are important for the future career of

accounting students, these skills are: written and oral communication, motivation,

decision-making, financial analysing and professional judgement.

Accounting companies are looking for employees who are not afraid of technology, but

who are creative and open-minded. These employees also need to know how to work

with and how to use the data provided by technology (Al-Htaybat et al., 2017).

Universities will have to work with companies to make sure the students learn the

required skills to work with Big Data. Accountants that are able to work with Big Data,

extract the necessary information and make the information useful at the right time will

be needed in the accounting field. Silverman (1966) explored the effect of automation

and came to the conclusion that automation destroys old skills, but at the same time

creates new skills that require the knowledge of how to use complex machines.

Accountants will have a more proactive role in the business and will be required to stay

in contact with employees working in different areas -like Information Technology (IT)-

(Coyne et al., 2017; Gamage, 2016).

According to Kokina et al. (2017) the following types of activities will exist in accounting

jobs:

- Working with machines to improve performance and results of the company;

- Overseeing the use of intelligent machines and determining if a different

automation tool is necessary;

- Working with vendors to develop Artificial Intelligent systems and to maintaining

the existing ones;

- Performing tasks that are still impossible to perform with automation;

- Performing accounting tasks, in which the use of an automated system would not

be efficient.

32

4.9 Implications on small accounting firms

Automation will be integrated in daily operations, therefor companies will have to invest

in technology to remain relevant and to survive against the competition in the twenty-first

century (Chase et al., 1991). Small companies do not always have enough capital to

invest in the technology, since the technology can be capital-intensive. This can create

problems for small accounting firms, as these firms cannot keep up with the bigger firm`s

investments in AI. Since AI is more efficient in performing routine tasks than human

intelligence, small firms are consequently less efficient than bigger firms that are able to

invest in AI and are therefore less competitive.

4.10 Implication on the labour market

Rattunde et al. (2016) examined the impact of automation on the employment in the

United States. Specifically, the authors analysed how computer-based technologies and

robotics have contributed to job polarization by reducing the number of “middle-skilled”

jobs, while reinforce employment in both low-and-high skilled jobs. This paper indicated

that automation did not reduce the overall employment. Automation has replaced some

tasks, but also complemented other tasks. Formalized and codified tasks have already

been automated, since machines represent less labour costs for the companies and are

more accurate and more productive. Tasks that require flexibility, judgment and common

sense are more complex to automate. Humans still have the advantage of being able to

make decisions in a situation of uncertainty. Some low-skilled manual jobs that require

language recognition, social interactions and situational adaptability are difficult to

automate, just as the high-skilled professions that require creativity, critical thinking and

problem-solving skills. Blum (1966) also reported that there has been an increase and a

decrease in the number of jobs requiring less skills, as well as both an increase and a

decrease in the number of jobs requiring more skills. Automation can replace some

tasks, but at the same time also create new tasks. The amount of blue-collar jobs

decreased compared to the white-collar jobs, due to the different skill requirements and

training. According to Blum (1966), technological unemployment affects especially young

workers, old workers, low-skilled and low educated workers. Workers who possess only

one skill in that specific occupation will have difficulties to develop new skills in other

occupations. Sorgner (2017) provided an overview of current trends and developments

on the labour markets due to the automation of jobs. This study also describes the most

recent dynamics of self-employment related to the risk of the automation of jobs. The

author reported that middle-skilled workers in routine jobs are more susceptible to

33

automation, while people with low and high levels of education are less likely to have

changes in their work occupation. Middle-skilled workers looking for a job will have to

possess or develop skills that are hard to automate, such as creativity or social

interactions. This paper indicated that people who are willing to take risks (like starting a

completely different job or developing new skills) have less probability to be unemployed.

4.11 Solutions

Kim (et al., 2017) described two temporary solutions regarding the change of existing

jobs and two long-term decisions concerning the creation of new jobs.

The first solution is to reduce work time of the employees. By decreasing the working

hours of each employee, the companies can maintain every employee and avoid an

increase in labour costs. Machines can do the work of a human more efficiently and

effectively. The machines will aid in reducing labour costs and enable a company to

lengthen working hours as the company improves its financial performance. The

retirement age could be reduced, opening job positions for young workers. The

employees will thus have more time to spend besides work and improve their quality of

living. However, reducing work time might provoke dissatisfaction of employees because

it represents less salary. Therefore, sharing work time with machines is only a temporary

solution.

Another solution is to propose social programs to the jobs that could be replaced by

technology. The susceptible jobs that could be replaced by automation are the jobs that

are relatively low paid and do not require much creativity. Hence, these unemployed

workers could be helped by programs provided by the government to motivate these

persons to work in another field. However, these programs are often expensive and

would be covered by taxes from citizens, entrepreneurs and capitalists. Thus, it would

help unemployment only for a short period.

The creation of new jobs proposed by the government could be a long-term solution. For

instance, accelerating the creation of new jobs by stimulating business through tax

benefits. Unfortunately, government programs are often seen as national

embarrassments and it represents a huge investment.

34

The most reasonable solution would be a change in education. The future employees

should have the necessary skills to work alongside machines and the current employees

should develop their skills to stay important in the company. The education system might

change by focusing on critical and system thinking and developing students’ creativity

skills. Students with the right qualifications are able to work with technology, instead of

being replaced by it.

35

5. Methodology Now all the literature regarding the future of the accounting is gathered, it is important to

test these results in an empirical study. First, the research design will be mentioned.

Then, the data collection methods will be discussed. Furthermore, the reliability and the

validity of this study will be described. Finally, the ethical considerations will be

discussed.

5.1 Research design

This study is a qualitative study. In quantitative studies, the results are derived from

numbers collected and statically analysed. In qualitative studies, verbal data and

experiences are necessary for completeness (Verhoeven, 2010). The benefit of a

qualitative study is that during the collection of the data, emotions, opinions as well as

human experiences are explored, which can contribute to a better understanding of the

subject.

5.1.1 Interviews

During this qualitative study, interviews have been conducted. Eight professionals have

been interviewed regarding their use of technology and their future perspective on the

accounting profession. The duration of the interviews differed from 25 minutes to one

hour and ten minutes, depending on the respondents and their available time.

5.1.2 Population

Since accountants have 94 percent of probability of losing their jobs within the next two

decades (Nagarajah, 2016), those professionals were selected to study the question if a

future in accounting without human intervention is possible. As mentioned, a total of eight

interviews have been conducted, in which eight accountants were interviewed. One

respondent stated to remain anonymous, in order to protect the clients’ information

shared during the interview. The names of the companies of other respondents have

been given.

5.1.3 Place

As mentioned earlier, interviews with professionals from Belgian and Luxemburgish

companies have taken place.

36

5.1.4 Description of the respondents

Respondents Years of Experience Title When Where How Duration

Binder Dijker Otte (BDO)

13

Senior Manager / Accounting & Reporting

services

12/03/18 Brussels In person 1h06

Deloitte 19 Partner /

Accountancy & Advisory

6/03/18 Ghent In person 1h10

Deloitte 18

Director / Accounting & Corporate

Services

29/03/18 Luxembourg In person 1h04

Lo Presti Ludovic (LPL) Experts-comptables

14 Manager /

Shareholder 17/04/18 Luxembourg In person 25 min

Klynveld Peat Marwick Goerdeler (KPMG)

22

Partner / Financial

Services Tax 19/04/18 Ghent Telephone 32 min

Mazars 11 Director /

Accounting department

9/05/18 Ghent In person 36 min

Anonymous 29 Director /

Tax & Legal Services

22/05/18 Ghent In person 39 min

University of Luxembourg 20

Head of Finance and Accounting department

31/05/18 Luxembourg Telephone 58 min

Table 6: Description of the respondents

37

5.2 Data collection

The data collection methods that have been used during the empirical part of this study

are semi-structured interviews and a systematic literature study.

5.2.1 Semi-structured interviews

Because the experiences of the respondents are important while studying the future of

the accounting profession, the researcher has chosen to use semi-structured interviews.

This type of interview involves the use of an interview guide, a written list of questions or

topics that will need to be covered during the interview (Saunders, Lewis & Thornhill,

2009). The order of the questions may vary from interview to interview. For eight semi-

structured interviews is chosen, because this number of interviews seems achievable

regarding the given time period of this study and because this number contributes to the

reliability of this research. While interviewing respondents, the years of experience and

the profession title have been described.

The following topics take a central role in each interview: the use of automation within the

firm, the role of the accountant, the qualitative characteristics of the financial information,

the skills of the accountant and the small accounting companies.

It is important to show the interview results as detailed as possible, without omitting or

modifying the text and thus the context. The interviews have been analysed in a

consciously way. After all, it is a qualitative research in which qualitative analysing is

necessary.

The result of the interviews have been processed in the following way: The interviews

are audio-recorded and afterwards transcribed, meaning that the interviews have been

written down on a document using the actual words of the respondents (Saunders et al.,

2009). Then, the answers are per respondent divided in small fragments. This process is

necessary to assign a code to the fragments with a term. By coding the fragments, an

overview has been created (Boeije, 2010).

In annex 3 the interview guideline can be found.

5.3 Reliability and validity

In order to provide sufficiently consistent and relevant evidence, the quality of a research

must be both reliable and valid. How the reliability and validity of this study have been

ensured, will be clarified in this paragraph.

38

5.3.1 Reliability

Mistakes during a qualitative study can happen accidentally. The reliability of the

research results indicates to what extent the research is free of mistakes. To test the

reliability of the study, the study should lead to the same results if another researcher

would repeat the study. If it leads to the same results, the research is reliable

(Verhoeven, 2010).

The reliability of the semi-structured interviews has been guaranteed by holding trial

interviews. The advantage of holding trial interviews is that the interview questions can

be tested. In this way, the questions asked to the respondents of the empirical study

have been adequate.

During the interview unprepared questions have been added, which allowed the

interviewer to add and expand on answers given to get a more realistic and honest

response.

To avoid unnatural responses to questions due to unavoidable effects -like anxiety- the

transcribed interview has been sent shortly after to the respondent to guarantee that the

transcription represents a true reflection and is free of errors.

The reliability of the study has been increased by the usage of a recording device.

Recording the interview avoids the risk of interpretation of notes and enables the

interviewer to listen to the interview again and thus to report correctly. However, if the

respondent would not have felt at ease to mention something due to the recording, the

recording would have been ended.

5.3.2 Validity

The validity of a research shows to what extent the research is free of any error

(Saunders et al., 2009). There are three types of validity: internal validity, external validity

and construct validity.

5.3.2.1 Internal validity

The internal validity implies that the collected data represents the reality (Verhoeven,

2010). To increase internal validity of the data, various steps are taken. Hence, the

choice of interviewing experts who have experience in the accounting field increases the

credibility of the results. Internal validity can also be established by increasing the

number of interviews. The greater the number of interviews, the more reliable is the data

collected. Furthermore, the recording of the interviews enables to transcript the whole

39

conversation and avoids errors or missing data. The transcribed interviews have been

returned to the respondents for reviewing and approving.

This study uses triangulation. Triangulation is the use of multiple data collecting

methods, in this case a systematic literature study and semi-structured interviews. The

advantage of triangulation is that data provided by multiple sources increases the

accuracy and validity of the research (Verhoeven, 2010).

5.3.2.2 External validity

By external validity is meant if the chosen sample gives the correct reflection of the

(accounting) population. If that is the case, then the data collected can be generalized

(Verhoeven, 2010). When talking about qualitative research, the size of the chosen

sample is often insufficient to be representative for the whole population. In this case, the

group of respondents is too small to claim the representativeness of all accounting

companies in Belgium and in Luxembourg. However, a lesser external validity does not

necessary mean that nothing can be done with the results of a research (Verhoeven,

2010).

5.4 Ethical considerations

It is important to follow ethical considerations when it comes to dealing with interviews.

During the collection of data, the identity of the respondents has been protected through

anonymity, unless the respondent agrees on publishing personal information. A reminder

of the research subject has been mentioned before each interview. The consent of the

respondent to an audio-recorded interview has been requested. Each respondent has

been given a written version of the discussion. The information obtained during the

interview has been reported in all honestly. The company of the respondents have been

kept confidential, unless indicated otherwise.

The signed confidentiality agreement can be found in annex 4.

40

41

6. Results In the sixth chapter, the description of the results will be given. Furthermore, the results

from the semi-structured interviews will be described.

6.1 Description of the results

Eight interviews were conducted (three directors, two partners, one senior manager, one

manager and shareholder). The years of experience vary from 9 to 29 years. Four

interviews were conducted in Belgium and four in Luxembourg. Individual interviews took

place face-to-face (n=6) and via telephone (n=2) between March 2018 and May 2018.

6.2 The use of automation in the company

Years of use

Reasons for using automation Automated tasks

BDO Brussels 4 – 5 years

• Quality • Time saving • Productivity • Pressure from market

• Scanning • Bookkeeping • VAT treatment

Deloitte Ghent 6 – 7 years

• Time saving • Pressure from market • Quality

• Bookkeeping • Tax compliance • Mutual share of

information with clients • Reporting

Deloitte Luxembourg +2 years

• Time saving • Quality • Pressure from market

• Scanning • Bookkeeping

LPL Experts-comptables /

• Time saving • Pressure from market • Quality

• Scanning • Bookkeeping

KPMG Luxembourg

+/- 15 years

• Efficiency • Pressure from market

• Tax return

Mazars Ghent 4 – 5 years • Pressure from market • Accuracy • Time saving

• Scanning • Bookkeeping • Miscellaneous operations

Anonymous 10 – 15 years

• Eliminate administrative tasks

• Focus on tasks added-value tasks

• Administrative tasks • Bookkeeping

University of Luxembourg

3 years

• Enhance management • Regulatory need • Credibility • Time pressure • Costs saving

• Financial accounting • Cost accounting • Budget

Table 7: Overview of the use of automation

42

BDO Brussels is using automation since about five years. According to the respondent,

automation plays an important role in their business. All invoices are scanned and go

immediately into the system and are booked if the system recognizes the documents. In

this way, the invoice is directly linked with the account and booked automatically. The

same is done with the VAT extracted from the invoices. Technology is developing

extremely fast, human intervention is almost not needed for many tasks. Earlier, human

intervention was needed to understand what happened in the past and to predict the

future. Today, software is already able to understand this and thus predict the future.

Automation might take decisions for people. The most difficult is that no matter what kind

of automation a company has, the competitors will have it as well. The business model of

a company will have to change to be able to compete against competitors. Pressure from

the market exists and avoiding the use of automation is not possible anymore. The

choice of implementing automation is a strategic choice made by BDO Brussels. By

using automation, the productivity and the quality increase. Employees spend less time

in bookkeeping and can focus more on other tasks.

Deloitte Ghent is using automation since almost seven years. Automation at Deloitte

Ghent starts already with the identification of their clients, like the ID card, notarial act,

VAT number, etc. All those documents are combined and gathered in a digitalized

system. The company makes sure that not everybody is able to access that information,

in order to comply with the General Data Protection Regulation (GDPR). Their

accounting system is fully digitalized with the use of different software, like the “BOB”

software combined with “Exact Online”, as well as “Silver Creek” which enables to import

sales data from clients and purchased invoices. Deloitte also uses “CODA” for the

statement of bank accounts. The firm is now working on software to deliver each client a

fully automated reporting. Finally, another phase the company is working on is to share

all data mutually with the clients, so that if the client needs a document or if Deloitte

needs a document from the client, the system already has it. According to the

respondent, the benefit of using automation is that the company can work faster and thus

save costs. The employees have more time for important tasks like the calculation of tax.

The clients know how automation is evolving, companies are forced to work with

automation. The clients are not willing to pay for basic tasks anymore, as in the past.

43

Automation at Deloitte Luxembourg is being used since a long time but according to the

respondent, the automation process has been accelerating in the last two years.

Automation is used generally for the treatment of documents. The firm used to spend

much time on the treatment of documents and on sending the mails to the responsible

person. Now each document is received by mail, which creates a more fluid process. A

system is used for the account statements. For instance for bank operations, once the

bank validates a transaction and it has been paid, it is entered in the accounting system

automatically. In this way, the company saves a lot of time. The costs for personal in

Luxembourg are quite high, hence each process that can be automated -and thus avoid

time that employees spend on unnecessary tasks-, will be. Secondly, automation

enables to step up the quality of the services. Once a repetitive task has been

performed, there is no added value in doing it again. The machine will replace the

repetitive tasks and the employee will be responsible for tasks that add value. Reasons

for companies to invest in technology are either when there is pressure from customers

or when there is pressure from competitors. The pressure comes generally from young

customers, who expect services provided by the latest technology. To attract clients,

companies can nowadays not ignore this demand. Automation is a continuous process

that is used step by step. At each stage of automation, the employees who are affected

by the new way of working are trained. “Automation is replacing what was done manually

before, by an automated process.”

Contrarily to the previous companies, LPL Experts-comptables Luxembourg does not

use much automation. The company used to work with a software which scanned the

documents and extracted information like the name of the client, the bank account, VAT

amount, etc. but “Winbooks” -a Belgian accounting software that is used in the company-

is not yet adapted for the usage in Luxembourg. Hence, the company only kept the

scanning process, meaning that the clients send the document per mail and the files are

automatically linked with the account. The reason the company uses automation is

mainly to increase the quality of reporting and because of the demand from clients to

facilitate the accounting. Clients are looking for serenity and advice. The more the client

is seduced, the greater the satisfaction. The employees do not receive training, but a

presentation of the accounting software “Winbooks”. Since the software is not difficult to

understand, training is not considered required.

44

KPMG Luxembourg uses automation since about fifteen years. The tax department uses

automation for the tax return. Tools are being developed to increase efficiency. The goal

is to extract the accounting data directly from the systems and automatically create tax

returns. Efficiency is one of the reasons for using automation. Not every task can be

automated, but tasks that are repetitive -and thus not interesting for employees- can be

replaced. Customers demand to have automatic solutions at a lower price. If the

structured tasks are automated, a reasonable price can be offered and the company can

be more competitive. The employees of KPMG Luxembourg receive two different

trainings. The first training is a more formal training and the second one is the “learning

by doing”, with the supervision of an experienced employee. The “four eyes” method is

applied, meaning that there is always a more experienced person who has to supervise a

junior and validate his work.

Mazars Ghent is using up-to-date automation as much as possible. The company started

to use automation since 2013-2014. Scanning and having electronically documents in

the system is the most used automation process in the company. The company tries to

avoid manual input. Regarding the scanning, Mazars Ghent has an external partner who

comes once or twice a month to pick up documents. The external partner scans and

returns the documents and Mazars receives the documents electronically in the cloud

platform where modifications can be made. The firm automates bookkeeping for

invoices, accounts receivables, accounts payables and bank accounts. There are some

issues with automating foreign bank accounts, but regarding Belgian bank accounts the

process is completely automated. Miscellaneous operations, like depreciations and

amortisations, are fully automated as well. The automatic process enables the company

to work on added value tasks, for which the clients agree to pay. The input process does

not produce any added value and needs to be done by automation, while the analysis of

figures and a management reporting -that is produced faster and more accurate

compared to humans- creates more value. The annual reporting is performed much

faster than in the past. Every employee who starts working at Mazars Ghent receives a

standard training of one day before having seen the accounting systems. Additionally, a

second session is organized when the employees have already worked with the system

and can ask questions.

45

Anonymous is working with “soft” automation since ten to fifteen years and with new

technologies, like robotics, since one to three years. The aim of using automation is to

get rid of the administrative tasks, which are easy to automate since the tasks are “rule

based”. Considered as administrative tasks are: emails sent, the data collected from

clients, the approvals collected from clients etc. The company believes that in a few

years there will be less manual intervention in data collection and in handling this data,

as it is the case with the scanning process. Nowadays, accounting companies are using

the scanning because it became a usual way of doing the bookkeeping. The digitalized

bookkeeping became normal; typing an invoice in the system is nowadays not

imaginable. The same will happen to the administrative tasks. Accountants need to focus

on tasks that add value and where knowledge is needed to make decisions. The

employees of Anonymous receive several trainings instructed by IT teams. The training

can either last for one week or multiple weeks. Since automation is new, every employee

receives training. During the training, business cases are analysed in teams.

The accounting department of the University of Luxembourg is using automation since

2016 and the human resources department since 2015. As a public entity, the University

receives significant funds. A multi-year contract is signed with the State and the Key

Performance Indicators (KPI) must be respected. To be able to give the State an

overview of the budgets, the University needs to get a fast budget follow-up from the

system. Furthermore, the entity is also reviewed by the Court of Auditors, which also

verifies the budgets. As a research entity, external funds are needed for the research

projects. Thus, it is important to have some credibility to attract potential investors.

Moreover, with the limited time of reporting, the University needs to have a quick

understanding of the budget to make appropriate reports. The pressure on the costs is

another reason for using automation. Automation enables to have a better understanding

of the costs and achieve certain goals. The University is currently working with the “SAP”

software. The University uses different modules available in the software. First, the

Financial Accounting (FI) module is used for invoices, expenses, closure of the accounts,

capitalization and amortization of tangible and intangible assets. Then, the Controlling

(CO) model is used for cost accounting. The University is also currently using the Project

System (PS) module. As a research unit, the University has many research projects

funded by the European Union or by the National Research Fund. Through this module,

the University is able to get an annual budget vision and a multi-year budget vision. The

software enables to record expenses and revenues and thus the University immediately

46

has an overview of the available budget. If the University does not have sufficient budget

available, the system will block the purchases. Automation is also used for Human

Resources Management and payroll management. Every employee is registered in the

system. Each of the employees has an identification in the system and their skills and

degrees are registered as well. The salary is hence paid based on their title job. A

Timesheet will be soon installed to report the time spent on the tasks.

The employees of the University will receive training to be able to work with automation.

The entity is now focused on communicating with the employees to make them aware of

the future changes. First, the University wants to see the reactions of the employees to

identify the right people to train. Then, a presentation of the process will be described by

an external service entity. The employees will receive a PowerPoint presentation and will

have direct access to the program so it is possible to start using and testing the software

and ask questions immediately.

47

6.3 Qualitative characteristics of the financial information

Relevant Comparable Faithful Understandable Timely Verifiable

BDO Brussels X √ X √ √ √

Deloitte Ghent X √ X X √ √

Deloitte Luxembourg X √ X X √ √

LPL Experts-comptables √ √ X √ √ √

KPMG Luxembourg X √ X X √ √

Mazars Ghent X √ X X √ √

Anonymous X √ X X √ √

University of Luxembourg X √ X X √ √

Table 8: Overview of the qualitative characteristics

According to Deloitte Ghent, the financial information is not always reliable, because on

one hand, accountants do not have enough data to be sure that the information is

correctly reported. On the other hand, accountants might be measuring the wrong data.

One cannot know if the chosen algorithm is the right one. It is also a matter of choosing

the right provider and the right tool. By choosing small software as a big company, it is

more likely to find some issues. However, by choosing software that is already proven to

be reliable by users and tax authority, the reliability does not need to be questioned. A

faithful representation of a company cannot be made without any human intervention

during the automated process, states Deloitte Luxembourg. Automation will help the

accountant to do what is predictable and repetitive, but human intervention is still

necessary because accounting is a profession where judgment is needed and

unforeseen situations happen. If a machine would perform every task without a human

reviewing, there will be a risk of making errors. The errors exist because the person

writing the algorithm is a human (who can make mistakes). The error may be a wrong

rule given to the machine and hence will lead to an incorrect configured process.

However, once the machine is well configured, errors will not take place. Moreover, the

48

accountant needs to use automation to reduce the chances of human errors. A person

who is tired can make mistakes. A machine, in contrary, does not get tired and preforms

like usually. Furthermore, as described by Mazars Ghent, by using the scanning process,

the files go directly into the system without -in principle- any human intervention and thus

human errors can be avoided. This is only applicable for the basic information of an

invoice, like supplier- and customer dates. The rest of the information can be wrong and

needs to be reviewed by an accountant. The same applies for the “Blockchain”.

According to KPMG Luxembourg, the digital ledger reduces the risk of small errors but

will never be entirely accurate. “The advantage of automation is that it almost wipes out

every small error, so that accountants can verify if there are mistakes by taking a sample

of the biggest and most complex transactions, which enables to reduce the errors in big

transactions”, reports Mazars Ghent. According to Anonymous, “the biggest problem with

most of the accounting companies is to know if the provided data is correct. A lot of data

has been processed in the Shared Service Centre -a centralized point of service that is

responsible for operational functions, like administrative tasks (Gartner, n.d.)-, meaning

that employees need to keep in mind that mistakes can happen”. Employees need to

know if the provided data is correct before validating the data, but this is often difficult to

determine. The financial information will be reliable if the analysis and verification

continues to be done by a human, states the University of Luxembourg. Perhaps 80

percent of the accounting will be automated and 20 percent that will be performed by a

human. Automation can create errors but by performing tasks manually, there are more

errors.

According to Anonymous, the information extracted out of the system is easier for

accountants to understand and better decisions can be made because of it. The

computer program provides standardized data and when mistakes occur, accountants

need to know how the information has been processed. In order to make information

understandable, Deloitte Luxembourg suggests that managers and Chief Financial

Officers (CFOs) should make a specific reporting for the needs of investors, by grouping

some positions of the financial statements including specific names of certain positions

and data and statistics, which will enrich the presentation of accounting data. Employees

need to know what has been done with the data and how the system came to the results.

Therefore, KPMG Luxembourg is paying attention to the “user experience” of software.

Before using software, the company considers questions like: is the software easy to

manage? Is it initiative? Is the information easily understandable? It is important that the

49

users of the report understand the analysis of the financial information. According to the

University of Luxembourg, by using efficient software that provides standardized data,

the information will be easier to understand.

According to Anonymous and BDO Ghent, automation provides a huge amount of data

and also suggests solutions to the data collected. It is difficult to determine if the given

solution (by automation) is needed, since the information might not be relevant.

Structuring the data with the client enables the accountant to take the right information

out of the system and uses only relevant information for the financial statements, reports

Anonymous.

According to the respondents, the report produced by automation is realized faster, since

the introduction of the scanning process. Before automation, time was wasted by waiting

for the documents sent by clients. Furthermore, the documents arrived by post -not per

email-, so the files needed to be distributed as well. Nowadays, the monthly report can

be done more smoothly over the month, without having to rush at the end of the month

when the necessary documents are received. The companies already have the files

needed in the system and can start the monthly report sooner than before. Because the

process is nowadays faster, the same work can be done by less employees.

As stated by Deloitte Luxembourg, automation can improve verifiability because the

documents are available and controllable at any given time, since the paper documents

are converted into electronic documents. According to the respondent of Mazars Ghent,

automation makes it easier and more accessible to find the documents needed with a

search tool. Furthermore, the risk of loosing a document rarely exists. The risk of

digitalized documents, however, is that the documents can be manipulated. Therefor, an

electronic document is only valid when the original document can be authenticated. The

respondent of BDO Brussels points out that “since automation replaces verification

procedures it consequently results in increased output quality. In that view automation

does not have a direct impact on verifiability but has an impact on the need for

verification. If the procedure is correct, you need to do spot checks to see if the intended

procedure still holds, but you are not required anymore to be able to verify each

document.” This means that automation will already be responsible for the verification

procedure and there is no need to verify each document anymore since the documents

are already controlled by automation. The verifiability should hence not be an issue, only

50

the verification procedure of the computer program should be verified. With automation,

each procedure needs to be documented and each document becomes a reference,

reports the respondent of the University of Luxembourg. This means that the traceability

of the documents has improved. In the past, much time was spent on searching for the

documents and making the link with the accounting transaction.

Automation enables to improve comparability, because automation allows an easier

comparison between different periods. There is no longer the need to search documents,

since the documents are already linked to the software used, reports Deloitte

Luxembourg and Mazars Ghent. Software’s that can analyse data enhance the

productivity of comparing different periods. Analysing data takes more time if it is done

by hand, thus a computer program -that can analyse a big amount of data- is beneficial.

Furthermore, without automation, accountants had difficulties to compare the financial

statements from one period to another when some modifications in the accounting

process were done. Sometimes, modifications were not even known by accountants and

needed to be identified first and then finally be compared. By using automation, the

process is standardized and the changes are easier to identify. Nevertheless, according

to BDO Ghent, the cut-off could be a problem: when an invoice is received in September

but the good was bought in January, the costs should be booked for January. This

process is still difficult to automate.

51

6.4 Skills

Automation cannot perform

Skills accountants need to develop Future role

BDO Brussels

• Interpretation • Decision-making

• IT • Programming • Social • Strategic

• Compliance • Advisor

Deloitte Ghent

• Advisory • Social • Interpretation • Thinking

• IT • Digitalization

• Advisor

Deloitte Luxembourg

• Decision-making • IT • Accounting

regulations • Market knowledge

• Advisor

LPL Experts-comptables

• Automatic integration of data

• Thinking • Tax knowledge • Judgment • Control

• None • More productive

KPMG Luxembourg

• Handle exceptional situations

• IT • Social • Organization

• Advisor

Mazars Ghent

• Expense notes, visa statements, etc.

• Closing entries

• IT • Excel • Social • Tax

• Advisor • Consultant

Anonymous

• Reasoning • Knowledge • Cross

competences

• Tax • Management • Selling • IT• Analytics

• IT • Consultant • Advisor

University of Luxembourg

• Analytical skills • IT • Analytics • Critical-thinking

• Analyst

Table 9: Overview of the skills

According to BDO Brussels, automation is currently not sufficiently developed for

interpretation and decision-making because certain data is needed to make decisions. It

could be possible, but a big amount of data is needed to make a correct interpretation

and decision. In the near future it might be possible that automation will be able to

perform these two tasks, although it seems difficult. Nevertheless, many tasks that

accountants used to do will be eliminated, but a lot of new tasks will be created as well.

Accountants with IT skills, with personal skills and a strategic view will be needed in the

coming years. The demand in IT skills might disappear after a while, as programming is

52

becoming easier. In the future, some accountants will shift to advisory and compliance.

The fear of disruption of the accounting sector exists due to the fact that there is already

some disruption going on. Accountants who are not afraid of change and see it as an

opportunity to shift to advisory or compliance, will not likely lose their jobs. The ones who

are scared and do not want to change might lose their jobs because non-skilled

employees with knowledge in automation can perform the tasks high-skilled employees

used do perform. As the respondent of BDO Brussels reported during the interview,

“high-skilled people are needed to increase the quality of reporting, as well as increase

the speed to be ahead of the competition. The challenging thing is what is needed to be

ahead of the competition. How can you forecast better? How can you change the skills of

the company to respond to the market? I am not sure that every accountant will go into

that direction.” Experts for analysis and interpretation will be needed. Nevertheless,

adequate skills for those tasks will be required. Programming and IT skills should be

acquired already at school. Universities should adapt to the market expectations and

foresee the appropriate lessons.

According to Deloitte Ghent, if companies do not make the shift to advisory, their

business model will be impacted. “Digitalization is not a threat for employment, it is an

opportunity for employment”. The way the accountants work is changing, but there will

not be a loss in jobs. In order to replace the accountant, it is important that a machine is

able to understand and have a good picture of each client’s situation. Nowadays,

technology cannot provide this way of working to the client. Furthermore, a machine

cannot communicate with people like humans do. The contact with the client is very

important to make the client feel at ease. Automation should not lead to a loss of contact

with clients. Besides, automation cannot think like a human and thus replace the

accountant in each task. The technology might make huge progress in the following

years, but at the moment it is difficult to adopt the vision of automation replacing

accountants for these tasks. However, basic tasks performed by accountants will be

replaced. To stay meaningful, accountants will need to develop IT-skills and digitalization

knowledge. Hence, universities should change and add courses in order for accounting

students to learn how to work with automation. IT and accountancy will be a combined

process in the future and accountants will need to be open to this new way of working.

53

Non-repetitive tasks cannot be automated according to the respondent of Deloitte

Luxembourg. The decisions taken by accountants differ from situation to situation. This

means that automation can perform what is called “rule based” tasks, where the software

is told what the consequence Y must be, if event X occurs. However, a skill that an

accountant has -and automation will never have- is the treatment of exceptional

situations. The accounting environment changes quickly and learning a machine how to

manage exceptional cases is unimaginable. Unless having an unbelievable smart

machine, which is not the case yet, the accountant will keep having an important role in

the company. There are studies that say that the accounting is one of the industries

where the risk of automation is the highest. The accountants’ tasks are seen as the

easiest to automate and therefore accountants could disappear. Indeed, there is a

category of work that will disappear, but the accountant himself will not disappear and

will have a different role in the company, for instance in advisory. The input of invoices

will be performed by automation, so that the accountant can focus on analysing and

advising the client on the financial statement of his business. Of course, some

employees are not willing to change their role in the company. Those accountants risk

being replaced once the technology becomes superior. Since the role of the accountant

is changing, their skills must change as well in function of the environment in which the

accountant works. Nowadays, an accountant needs to understand each different

business and market environment in order to be able to advise, anticipate and have good

knowledge of the accounting regulations. In addition, an accountant with IT-skills is

necessary to understand the different accounting software. More and more employees

realize that what is learned at university, does not match the reality. According to the

respondent “it is important that students learn how to handle exceptional situations, but it

is also important to give them a basic background in IT in order to be comfortable in the

computerized world.”

According to LPL Experts-comptables, the automatic integration of data into the

accounting software is the most difficult task to be automated. The scanning process

recognizes and understands most of the time the information on the invoices, but human

intervention is still needed for the review because errors still occur. A purchase invoice

can be booked differently depending on the amount or service. However, the machine

might not be able to recognize the correct account. The recognition can only be

automated properly if the supplier provides the information of the account on the invoice.

Moreover, tax knowledge, the ability of control and judgment is extremely important in

54

accounting. Then, as mentioned earlier, the recognition of the information on the invoice

is a problem as well. A computer cannot recognize if the supplier made a mistake on the

invoice regarding the title of the invoice or the VAT rate. Knowledge and critical thinking

is needed during the bookkeeping, even though many steps in bookkeeping are already

automated. Automation enables to work in a different way and increases the quality of

work, although technology will certainly never be able to replace the accountant

completely. Since the last five to ten years, the profession already changed a lot.

Accountants are required to be more productive than before, because automation allows

them to be so. Thus, junior accountants who already know how to use the different

accounting software have a big advantage. Any other skill is an advantage, but this does

not necessarily mean that accountants need to develop their skills to remain important.

According to KPMG Luxembourg, automation is already able to perform many tasks.

However, when it comes to dealing with exceptions, it is more difficult. The accountant

stays necessary for the supervision, for the control and for handling exceptional

situations (which automation cannot manage yet). On the other hand, depending on the

level of Artificial Intelligence, possibly one day a robot will take over the humans’ job and

employees will stay at home. As the respondent says, “The Blockchain is a revolutionary

technology, which can render a number of professions obsolete.” Each manual task will

be performed by a robot and intellectual tasks will be replaced by computer software.

The accountant will rather be an advisor than a bookkeeper. The skills of an accountant

will thereby have to change as well. An accountant who has knowledge about computer

software, who is very well organized and is a very good seller, will remain important for

the business. It is a combination of different talents and not only one. It would be best for

future accountants to acquire these talents already before starting to work, because

automation is the reality.

The respondent of Mazars Ghent reports that expense notes and visa statements are

currently the most difficult to automate, although it is not impossible with the right tools. A

manual entry is still needed to correct the accounting treatment. Closing entries and

exceptional operations will -according to the respondent- not be automated any time

soon, because human intervention and human analysis are still necessary. “Once we will

have an uniform invoicing system, there will be no need of human intervention.” The

repetitive tasks do not add value and are already automated and will certainly continue to

be automated in the future. Employees who do not want to make the shift to advisory or

55

consultancy and do not see automation as an opportunity, might risk being replaced by

automation. Accountants are becoming more and more consultants and sales people.

Tax and social skills are important for an accountant to have for consultancy services.

The accounting industry will need more competent IT employees for the analysis of the

figures and the management reports. ”Learning how to use automation before starting to

work and to have more IT skills would be an advantage for people.” The curriculum

students have was acceptable five to six years ago. Nowadays, it is not the case

anymore. Students need to learn how to use automation before starting to work. Big data

increases constantly and requires the analysis of it. There is software that can analyse

Excel files, but students need to be able to understand how to work with the servers and

link the software with the Excel files.

According to Anonymous, the difficult tasks to automate are tasks that require reasoning,

knowledge and sometimes cross competences. For instance, a task that involves tax

knowledge and accounting knowledge. Furthermore, consulting is complex to automate.

However, the company is working on receiving consulting advises from a robot. Hence in

the future, the task will be automated. “The ideal accountant is the IT guy with accounting

and tax knowledge, with good management skills and selling skills”, reports the

respondent. It would be ideal to have an accountant with all those skills, but that would

be impossible. The role of the accountants within the company is changing. Some

accountants are shifting to the IT environment, while others are moving to consultancy

and advisory. In the future, accountants will need to understand figures and analyse

them, meaning that analytical skills will be required. It is important that future

accountants have knowledge in IT and in the bookkeeping process. In the past, a junior

accountant would start by bookkeeping for a few years and would progressively shift to

more important tasks. Nowadays, a new employee already starts by doing important

tasks like the structuring and the analysis of figures. This means that bookkeeping will

not be performed at work and that the starting accountant should already posses this

knowledge.

The respondent of the University of Luxembourg believes that tasks that require

analytical skills, like the analysis of budget variances and miscellaneous accounting

operations, are difficult to be automated. Each task that requires the analysis of the data

cannot be automated, at least not at the University of Luxembourg. Accountants will

focus less on the treatment of documents and more on the analysis work for instance tax

56

analysis or analysis of the cost price, which will be more meaningful for the accountants

affected to this task. According to the respondent, not every accountant has the skills to

become an analyst. Accountants will have to understand how the software books each

invoice and identify possible mistakes. Critical-thinking, analysis and understanding of

the financial information will be skills required in the coming years. Although accounting

and financial theory will always remain important, IT skills will become even more

important in order to be able to work with automation.

57

6.5 Small accounting companies

Table 10: Overview of the small accounting companies

BDO Brussels states that some small accounting firms are managed by people older

than 60 years who think that automation is only for younger generations and avoid using

it in their company until they retire. Generally, the small firms do not invest in automation

because of the unawareness of the importance and the fear of change. It is a matter of

not understanding and not wanting to know how to use these new technologies.

As the respondent of Deloitte Luxembourg reports “some people do not feel comfortable

to know that their accounting data is somewhere in the cloud.” The respondent believes

that small companies will not have any trouble staying competitive, because small firms

will use software that is developed for them. Big companies usually invest a huge

amount in top-notch software and are therefore more difficult to replace due to the

invested capital. Small companies are able to replace the software by the latest

technology on the market, like “Cloud” or “Fintech”, because it is possible to not invest in

automation, but only to pay for the usage of automation. Most software is “Cloud” based,

meaning that the costs will depend on the number of documents the firm scans. These

costs are divided over the year. According to the respondent of Mazars Ghent, “The

leaders of the companies believe automation is costly, but that is not correct anymore.

This was the case six years ago”. On the other hand, some firms do not have many

Difficulties to remain competitive

Reasons for not using automation

BDO Brussels √ • Age

Deloitte Ghent √ • Age • Resources

Deloitte Luxembourg X • Lack of IT Knowledge • Fear

LPL Experts-comptables √

• Costs • Lack of IT knowledge

KPMG Luxembourg √ • Mentality • Resources

Mazars Ghent √ • Fear • Age

Anonymous X

• Choice • Time • Investment costs

University of Luxembourg √

• Investment costs

58

employees working. Most of the time the employment is just sufficient to do the work, but

the resources available do not permit to invest in automation. In the coming years, small

accounting firms will have a very difficult time. The clients are looking for the cheapest

service provider. A company that does not use automation will have higher fees than a

company that uses software that enables to increase productivity and quality. There will

be a lot of pressure on the prices, which will lead to a risky situation for small accounting

firms. It is a choice made by managers of the companies. Everything depends on what

the vision of the manager is. Using automation also means investing time and money in

the procedure.

According to the respondent of Anonymous, before using automation, accounting

companies needed to buy the right tools, train the employees, transform their clients’ files

into this new way of working, have discussion with clients on the new way of working etc.

Automation enables to work more efficiently and it is not an expensive tool, but it does

not mean that it will be cheap the first time one will use it. The company needs to be

ready for automation, but their clients as well. There is a lot of work to do that requires

time and money and those two factors could be a reason for not using automation.

The implementation process requires a lot of settings and once the software is installed,

it is difficult for a company to change its mind on software and replace the software by a

new one, states the respondent of the University of Luxembourg. If a small company

does not really feel the pressure to use automation, if the clients do not demand it and

the pressure on costs is manageable, the firms will tend to push automation away.

59

7. Discussion Routine tasks are most likely to be replaced by automation, the technology is not yet

sufficient developed to replace the accountants in non-routine tasks, where critical

thinking and judgment is required (Oschinski et al., 2017). Accountants, as expert

decision makers, use their knowledge in unforeseen situations to make reasonable

decisions based on their experience. Automation is not capable of interpreting, judging or

making decisions. Nevertheless, some accounting companies are already developing

accounting tools by integrating Artificial Intelligence in automation. In the coming years,

automation will be assisting accountants in the decision-making process. Artificial

Intelligence is the technology that will revolutionize the profession of accountants.

Automation has enabled companies to increase in efficiency by eliminating the time

consumed in repetitive tasks, and can improve productivity by performing tasks faster

than a human. As Herbert et al. (2016) described, by focusing on more creative, non-

structured tasks, the value of the accountant’s contribution will increase. Bookkeeping is

one of the accounting tasks that is almost fully automated since the introduction of the

scanning process. Accountants can thus focus on added-value tasks, like the analysis of

figures and advisory. Al-Htaybat et al. (2017) reported that there will be a lot of pressure

on the prices, because clients expect to get the fastest reports, with the highest quality at

the lowest price. By replacing the repetitive tasks by automation, accountants can focus

on more added-value tasks. Companies are looking for efficiency and therefor need to

satisfy the clients demand (Gonzalez et al., 2012). The interviews confirm that clients are

looking for the companies that can provide the fastest report with the greatest quality and

the less expensive. As a consequence, accounting firms that provide services without

using automation -and are thus less efficient- will have difficulties because their prices

will be higher than the prices from the competition.

Automation has increased the quality of reporting, since it reduces the risk of errors

made by accountants (Herbert et al. 2016). However, errors still exist and a faithful

representation of the financial statements is only possible with human intervention. Each

qualitative characteristic which automation cannot do: relevance, understandability and

faithful representation.

A human interference cannot be avoided yet, although in a few years it could be the

case. Hence, automation will continue to compliment accountants, rather than replace

accountants. Furthermore, the financial reporting is produced faster since the

60

introduction of automation. The scanning process -which is used by most of the

companies nowadays- enables to start the financial reporting earlier than it used to be.

By scanning each document, the comparability and verifiability is enhanced. The

documents are available and controllable at any time. However, automation provides a

big amount of data, it is therefore difficult for accountants to know which information is

relevant for the accounting. Besides, accountants do not always understand the

information provided by automation, which makes it difficult to distinguish relevant from

irrelevant information. Nevertheless, automation is already able to provide solutions to

help accountants in handling the data.

In the coming years, accountants will have a different role in the company. Some will

shift to advisory while others will shift to consultancy. Accountants will have to develop

their skills to remain important. This evolution in skills will require different training and

education in order to keep adding value to the company. University will play a big role in

the future education of accountants. Parham et al. (2012) stated that IT, tax and

analytical skills will become very important. The results from the interviews confirm that.

According to Al-Htaybat et al. (2017), companies will be looking for accountants who are

not scared of changes and see automation as an opportunity rather than a threat. This

study shows that accountants who do not want to shift to another role within the

company are most likely to lose their job.

Although automation can already perform many accounting tasks, it cannot provide each

attribute of the qualitative characteristics that make the financial information useful.

Therefor, human interference will remain necessary during the accounting process to

provide a faithful representation of the financial information. Routine tasks are already

automated, while tasks that require creativity, critical-thinking and judgments will be

performed by accountants. Thus, the role of the accountant will change: the accountant

will perform tasks that add value to the company, like advisory or consultancy. IT-, tax-,

social- and analytical skills will have to be developed. Universities will need to change

their education programs in order for future accountants to be ready to work alongside

automation. Accountants, who do not want to obtain these specific skills, risk being

replaced by automation. However, accountants that do want to obtain these skills and

are willing to develop themselves will work alongside automation, rather than being

replaced by automation.

61

8. Conclusion This study examined the following research question: is a future in accounting without

human intervention possible?

In order for automation to replace accountants, financial information provided by

automation needs to be useful. The financial information needs to be relevant,

represented faithfully, comparable, verifiable, timely and understandable.

To examine the research question if a future in accounting without human intervention in

possible and if automation is able to provide useful financial information, a systematic

literature review and semi-structured interviews have been conducted.

32 articles were found useful and have been selected while conducting the systematic

literature review. The results showed that accountants will be using automation for

routine tasks, rather than being replaced by it. Tasks that require critical-thinking and

creativity seem to be more difficult to automate.

During the semi-structured interviews, eight interviews have been conducted with

accountants in different companies in Belgium and Luxembourg. The empirical study

shows that a lot of technological progress has been made in accounting since the last

decades. However, only the automation of routine tasks has been proven efficient.

Critical-thinking, creativity, analysing and judging are characteristics that the accountant

possesses that cannot yet be replaced by technology. Accountants will have a different

role in the company; some will shift to advisory while others will shift to consultancy.

Automation will replace tasks that do not add value (the so-called routine tasks), therefor

accountants are able to focus on more important tasks like the analysis of figures and

advising clients. IT-, tax-, social- and analytical skills will progressively become more

important. According to the respondents of the interviews, the main reasons for using

automation are: market pressure, time saving and quality improvement. Although the

quality of reporting improved since automation, errors still occur. A faithful representation

of the financial statement is not yet possible without human intervention. Relevance, a

faithful representation and understandability are the qualitative characteristics that

automation cannot provide yet without a human interference.

62

Artificial Intelligence or robots are the technologies that will revolutionize the accounting

profession. In the coming years, the technology will not only be able to replace

accountants in the repetitive tasks, but also to assist accountants in non-repetitive tasks

like during the decision-making process. The business model of accounting firms will

change, accountants will shift to advisory or consultancy and need IT-, social-, tax- and

analytical skills. Accountants who are not willing to obtain these skills will be at risk of

being replaced by automation. Universities will have to provide programs to prepare

future accountants to the new way of working.

63

9. Limitations Like every study, this research has some limitations.

Regarding the systematic literature study, only one researcher decided if studies were in-

or excluded. It is recommendable that more than one researcher decides about the

selection, this possibly would have led to another selection of articles to be read full-text. Another limitation of the systematic literature study is that none of the selected studies

took place in Belgium or Luxembourg, where the empirical part of this study took place.

Although the use of automation is a global development, no research has been found in

these specific countries and therefor it cannot be said without a doubt that results from

other countries are applicable in Belgium and Luxembourg. There might be cultural

differences between countries regarding the use of automation. Most of the selected

articles were written before 2016. Technology develops at a fast pace and therefore

results from some studies might not be up-to-date.

Regarding the empirical of the study, the semi-structured interviews have been

conducted in Belgian and Luxembourgish companies. A broader region would possibly

have led to more diverse answers from respondents. Furthermore, because of the time

limit, only eight interviews have been conducted for this research. The chosen sample

size is rather small. In order to generalise the findings, the number of interviews should

be greater. By interviewing professionals from different functions -for instance auditors-,

the results would possibly have led to different findings.

A strength of this research is that a systematic literature study preceded before the

interviews took place. By doing so, all relevant literature regarding the subject was

collected and the right interview questions could be formulated. Another strength of this

research is that the study took place in more than one country. Finally, only professionals

were interviewed during this study.

64

65

10. Future research It is recommendable that more research will be conducted regarding the question if a

future in accounting without human intervention is possible.

Most of the selected studies in the systematic literature study involved Expert Systems

and not Artificial Intelligence, it would be interesting to study how AI is used in accounting

and if it can solve the problems that automation cannot.

Moreover, it would be interesting to conduct a survey study, combined with in-depth

interviews to gain more insight into the use of automation in accounting companies and

the vision of a broader population on how the role of an accountant is changing. By

choosing a broader population, the results can be generalized.

Finally, it would be useful to interview IT-specialists who have deeper knowledge on the

technology behind the automation. By interviewing IT-specialists, it would be possible to

find out how the technology is developing and what automation will be able to perform in

the future. Hence, it would permit to have a better understanding of accounting tasks that

can or cannot be automated.

66

67

11. Management and policy implementations The current accounting profession will most likely (partly) change. As mentioned earlier,

automation can take over the routine tasks of accountants and perform these tasks more

efficient than human intelligence can. In that way, accountants are able to focus more on

the creative, non-routine tasks that require thinking and reasoning. As a consequence,

accountants will have a different role in the company: accountants will shift either to

advisory or to consultancy. IT-, tax-, social- and analytical skills will have to be obtained.

Universities will need to change their education programs in order for future accountants

to be ready to work alongside automation.

68

69

References Al-Htaybat, K. & Alberti-Alhtaybat, L. von (2017). Big Data and corporate reporting: impacts and paradoxes. Accounting, Auditing and Accountability Journal. 2017;30;4: 850 – 873, https://search.proquest.com/abicomplete/docview/1895189354/5A35144E18AF4EE6PQ/1?accountid=11077 Alexander, R. J. (2002). History of Accounting. Association of Chartered Accountants in the United States, https://www.uctoonline.sk/home/images/history%20of%20accounting.pdf Anonymous (1987, December). Expert Systems for Accountants: Has Their Time Come? Journal of Accountancy. 1987;164;6: 117 – 125, https://search.proquest.com/abicomplete/docview/206773139/15FCBB8B495849EDPQ/1?accountid=11077 Arntz, M., Gregory, T. & Zierahn, U. (2017, October). Revisiting the risk of automation. Economics Letters. 2017;159: 157 – 160, https://search.proquest.com/abicomplete/docview/1963430753/CCB84FD386F64FCFPQ/1?accountid=11077 Baldwin, A. A., Brown, C. E. & Trinkle, B. S. (2006). Opportunities for artificial intelligence development in the accounting domain: the case for auditing. Wiley Periodicals Inc. 2006;14;3:77 – 86, https://search.proquest.com/abicomplete/docview/214366383/E22DE3713D944462PQ/1?accountid=11077 Beaman, I. & Richardson, B. (2007). Information Technology, Decision Support and Management Accounting Roles. Journal of Applied Management Accounting Research. 2007;5;1: 59 – 68, https://cmawebline.org/images/stories/JAMAR%202007%20Winter/JAMAR-v5-1-Info%20Tech.pdf Blackline (n.d.). Accounting Process Automation: Automate repetitive, high-volume, and error-prone processes. Blackline, https://www.blackline.com/accounting-process-automation Blum, A. A. (1966). Job skills for automated industry. Management of Personnel Quaterly. 1966;4;4: 24 – 31, https://search.proquest.com/abicomplete/docview/195884331/EB3254574EE74EE8PQ/2?accountid=11077

70

Boeije, H. (2010). Analysis in Qualitative Research. SAGE Publication Ltd. https://books.google.be/books/about/Analysis_in_Qualitative_Research.html?id=z1Z0RIx-izwC&redir_esc=y Brands, K. & Smith, P. (2016, March). Ready or not, here comes accounting automation. Strategic Finance, http://sfmagazine.com/post-entry/march-2016-ready-or-not-here-comes-accounting-automation/ Business Dictionary (n.d.). Accountant. Business Dictionary, http://www.businessdictionary.com/definition/accountant.html Certified Practising Accountant Australia (2012). Management accountant. BPP Learning Media Ltd, https://www.cpaaustralia.com.au/documents/study-manual-management-accounting.pdf Chase, M. D. & Shim, J. K. (1991). Artificial Intelligence and Big Six Accounting: A survey of the current uses of expert systems in the modern accounting environment. Computers & Industrial Engineering. 1991;21;1-4: 205 – 209, https://search.proquest.com/abicomplete/docview/213753948/78209ACFB7D641A0PQ/1?accountid=11077 Chelliah, J. (2017). Will artificial intelligence usurp white collar jobs? Human Resource Management International Digest. 2017;25;3: 1 – 3, https://search.proquest.com/abicomplete/docview/1896372092/EC5D21B5325B43B8PQ/1?accountid=11077 Cole, R. C. Jr. & Hales, H. L. (1992, January). How Monsanto justified automation. Institute of Management Accountants. 1992; 73;7: 39 – 43, https://search.proquest.com/abicomplete/docview/229740261/E6655EEC355845C1PQ/1?accountid=11077 Coyne, J. G., Coyne, E. M. & Walker K. B. (2017, March). Accountants and Tech: Game changer? Strategic Finance. 2017;98;9: 40 – 47, https://search.proquest.com/abicomplete/docview/1891335404/57D6FBDB7D84BAAPQ/1?accountid=11077 David, H. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives. 2015;29;3: 3 – 30, https://search.proquest.com/abicomplete/docview/1753560993/A6BBAB3E9DAC4466PQ/2?accountid=11077

71

Deloitte (n.d.). Conceptual Framework for financial reporting. Deloitte Touche Tohmatsu Limited, https://www.iasplus.com/en-gb/standards/other/framework Dictionary (n.d.). Automation. Dictionary, http://www.dictionary.com/browse/automation Ernst & Young (2010, October). Conceptual Framework: Objectives and qualitative characteristics. http://www.ey.com/Publication/vwLUAssets/Supplement_86_GL_IFRS/$File/Supplement_86_GL_IFRS.pdf Ernst & Young, (2017). Intelligent Automation. Reshaping the future of work with robots. http://www.ey.com/Publication/vwLUAssets/ey-intelligent-automation/$FILE/ey-intelligent-automation.pdf Frey, C. B. & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change. 2017;114;C: 254 – 280, https://econpapers.repec.org/article/eeetefoso/v_3a114_3ay_3a2017_3ai_3ac_3ap_3a254-280.htm Galarza, M. (2017, February). The changing nature of accounting. Strategic Finance, http://sfmagazine.com/post-entry/february-2017-the-changing-nature-of-accounting/ Gamage, P. (2016, September). Big Data: are accounting educators ready? Accounting and Management Information Systems. 2016;15;13: 588 – 604, https://search.proquest.com/abicomplete/docview/1930956693/abstract/A96073C5C1A48A4PQ/1?accountid=11077 Gartner (n.d.). Shared Service Center. Gartner, https://www.gartner.com/it-glossary/shared-services Gonzalez, G. C., Sharma, P. N. & Galletta, D. (2012). Factors Influencing the Planned Adoption of Continuous Monitoring Technology. Journal of Information Systems. 2012;26;2: 53 – 69, https://search.proquest.com/abicomplete/docview/1266226166/D8A2083B697C4903PQ/1?accountid=11077 Hawker, S., Payne, S., Kerr, C., Hardey, M. & Powell, J. (2002, November). Appraising the evidence: Reviewing disparate data systematically. Qual Health Res. 2002;12(9):1289-99, https://www.ncbi.nlm.nih.gov/pubmed/12448672

72

Henry, B. & Hicks, M., (2015, August). A Survey of Perspectives on the Future of the Accounting Profession. CPA Journal. 2015;85;8: 10 – 12, https://search.proquest.com/abicomplete/docview/1712288049/B172E66D7B574E72PQ/1?accountid=11077 Herbert, I., Dhayalan, A. & Scott, A. (2016). The future of professional work: will you be replaced, or will you be sitting next to a robot? Management Services. 2016;60;2: 22 – 24, 26 – 27, https://search.proquest.com/abicomplete/docview/1797550349/515E90D4BECD4376PQ/1?accountid=11077 International Financial Reporting Standards (n.d.). The Conceptual Framework for Financial Reporting. International Financial Reporting Standards, www.ifrs.org/issued-standards/list-of-standards/conceptual-framework/ Institute of Chartered Accountants in England and Wales IT Faculty (2017). Artificial intelligence and the future of accountancy. Institute of Chartered Accountants in England and Wales IT Faculty, https://www.icaew.com/-/media/corporate/files/technical/information-technology/technology/ai-report-web.ashx Institute of Management Accountants (2008). Management Accountant. Institute of Management Accountants, https://www.imanet.org.cn/uploads/resource/2015-11/1447061510-17551.pdf Kim, Y. J., Kim, K. & Lee, S. (2017, March). The rise of technological unemployment and its implications on the future macroeconomic landscape. Futures. 2017;87: 1 – 9, https://search.proquest.com/abicomplete/docview/1898655308/C9FA06E36514124PQ/1?accountid=11077 Kokina, J. & Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is changing Auditing. Journal of Emerging Technologies in Accounting. 2017;14;1: 115 – 122, http://aaajournals.org/doi/abs/10.2308/jeta-51730?code=aaan-site Lee, J. D. & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46, 50-80, http://journals.sagepub.com/doi/10.1518/hfes.46.1.50_30392

73

Liu, Q. & Vasarhelyi, M. A. (2014, June). Big Questions in AIS Research: Measurment, Information Processing, Data Analysis, and Reporting. Journal of Information Systems. 2014;28;1: 1 – 17, https://search.proquest.com/abicomplete/docview/1712480134/4BE453E87124EA5PQ/1?accountid=11077 Manjoo, F. (2017, May). Google, Not the Government, Is Building the Future. The New York Times, https://www.nytimes.com/2017/05/17/technology/personaltech/google-not-the-government-is-building-the-future.html Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P. & Dewhurst, M. (2017, January). A future that works: Automation, Employment, and Productivity. McKinsey Global Institute, https://www.mckinsey.com/~/media/McKinsey/Global%20Themes/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx Marcello, S., Ray, T., Carmichael, D., Peterson, J. & Ramamoorti, S. (2017, February). The Future of Auditing: A Roundtable Discussion. The CPA Journal. 2017: 39 – 57, https://search.proquest.com/abicomplete/docview/1897267839/fulltext/8EEF96D6B3444739PQ/1?accountid=11077 Mason L. J. (1953, May). The Profession of Accountancy. Texas Technological College Library Lubbock, https://ttu-ir.tdl.org/ttu-ir/bitstream/handle/2346/20976/31295015076499.pdf?sequence=1 Minnesota Libraries (n.d.). Accountant. Minnesota Libraries, http://open.lib.umn.edu/exploringbusiness/chapter/12-1-the-role-of-accounting/ Moudud-Ul-Huq, S. (2014). The Role of Artificial Intelligence in the Development of Accounting Systems: A Review. The IUP Journal of Accounting Research & Audit Practices. Vol. XIII, No. 2,: 7 – 19, https://www.researchgate.net/publication/281115556_The_Role_of_Artificial_Intelligence_in_the_Development_of_Accounting_Systems_A_Review Nagarajah, E. (2016, July/August). Hi, Robot. What does automation mean for the accounting profession? Accountants Today, https://www.pwc.com/my/en/assets/press/1608-accountants-today-automation-impact-on-accounting-profession.pdf

74

Omar, K. E. M. (1993, April). Artificial decision-making and artificial ethics: A management concern. Journal of Business Ethics. 1993;12;4: 313 – 321, https://search.proquest.com/abicomplete/docview/198104896/6D259F58B1814801PQ/1?accountid=11077 Oschinski, M. & Wyonch, R. (2017, March). Future Shock? The Impact of Automation on Canada's Labour Market. C.D. Howe Institute Commentary. No. 472, https://ssrn.com/abstract=2934610 Oxford Dictionary (n.d.a). Artificial Intelligence. Oxford University Press, https://en.oxforddictionaries.com/definition/artificial_intelligence Oxford Dictionary (n.d.b). Big Data. Oxford University Press, https://en.oxforddictionaries.com/definition/big_data Oxford Dictionary (n.d.c). Machine learning. Oxford University Press, https://en.oxforddictionaries.com/definition/machine_learning Oxford Leaner’s Dictionary (n.d.). Expert system. Oxford University Press, https://www.oxfordlearnersdictionaries.com/definition/english/expert-system Özdoğan, B. (2017). The Future of Accounting Profession in an Era of Start-Ups. Accounting and Corporate Reporting - Today and Tomorrow, DOI: 10.5772/intechopen.69264, https://www.intechopen.com/books/accounting-and-corporate-reporting-today-and-tomorrow/the-future-of-accounting-profession-in-an-era-of-start-ups Parham, A. G., Noland, T. G. & Kelly, J.A. (2012). Accounting Majors’ Perceptions Of Future Career Skills: An Exploratory Analysis. The Clute Institute. 2012;5;1: 29 – 36, https://search.proquest.com/abicomplete/docview/1418437779/17409CFBA4E84A65PQ/1?accountid=11077 PriceWaterhouseCoopers (n.d.). Auditor. PriceWaterhouseCoopers, https://www.pwc.com/m1/en/services/assurance/what-is-an-audit.html Quinn, K. (1990). Expert System Shells: What to Look For. MCB UP Ltd. 1990;18;1: 83 – 86, https://www.emeraldinsight.com/doi/abs/10.1108/eb049088

75

Rattunde, E. S., Segura, J. III & Wallace, S. (2016). Technological change and job polarization: the wisconsin experience. Journal of Economics and Economic Education Research. 2016;17;2: 148 – 158, https://search.proquest.com/abicomplete/docview/1860687276/E0B31B2253FD4BD5PQ/1?accountid=11077 Sangster, A. (1994, June). The adoption of IT in management accounting: the expert systems experience. Journal of Information Technology. 1994;9;2: 159 – 169, https://search.proquest.com/abicomplete/docview/901453880/36E3A9DE5F154B02PQ/1?accountid=11077 Saunders, M., Lewis, P. & Thornhill, A. (2009). Research Methods for Business Students. (5th edition). Lombarda, Italy. Pearson Education Limited, http://eprints.stiperdharmawacana.ac.id/189/1/ResearchMethodsForBusinessStudents_Saunders.pdf Seek (2017, June). How automation is transforming the Accounting industry. Seek, https://www.seek.com.au/career-advice/automation-is-transforming-the-accounting-industry Silverman, W. (1996, June). The Economic and Social Effects of Automation in an Organization. The American Behavioral Scientist. 1966;9,10: 3 – 8, https://search.proquest.com/abicomplete/docview/194635665/abstract/FF2BED6E6B334A03PQ/1?accountid=11077 Smith, C., McGuire, B., Huang, T. & Yang, G. (2006, December). The History of Artificial Intelligence. University of Washington, https://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf Somayajula, S. (2017, August). Exit accountants, enter audit robots? The Hindu Business Line, http://www.thehindubusinessline.com/opinion/exit-accountants-enter-audit-robots/article9838692.ece Sorgner, A. (2017). The Automation of Jobs: A Threat for Employment or a Source of New Entrepreneurial Opportunities? Foresight and STI Governance. 2017;11;3: 37 – 48, https://search.proquest.com/abicomplete/docview/1944202601/4F9FC48C80974938PQ/1?accountid=11077

76

Staff, V. (2017, May). Google I/O 2017: highlights from the developer conference. The Verge, https://www.theverge.com/2017/5/17/15649204/google-io-highlights-2017-announcements-news Tual, M. (2017, March). A la rencontre de Watson, l’intelligence artificielle star d’IBM. Le Monde, http://www.lemonde.fr/pixels/article/2017/03/12/a-la-rencontre-de-watson-l-intelligence-artificielle-star-d-ibm_5093342_4408996.html Turing, A. M. (1950). Computing Machinery and Intelligence. Mind 49, 433 – 460, https://www.csee.umbc.edu/courses/471/papers/turing.pdf Tuzhilin, A. (2004, November). IT-Driven Automation: The Next Wave. New York University, http://www.academia.edu/24907622/IT_Driven_Automation_The_New_Wave Twentyman, J. (2017, March). Intelligent virtual helpers whittle away at human jobs. Financial Time, https://www.ft.com/content/54916686-f225-11e6-8758-6876151821a6 Tynan, D. (2017, August). What is machine learning? Software derived from data. InfoWorld, https://www.infoworld.com/article/3214424/machine-learning/what-is-machine-learning-software-derived-from-data.html Verhoeven, N. (2010, January). Wat is onderzoek? Praktijkboek methoden en technieken voor hoger onderwijs (3e druk). Den Haag, Nederland: Boom Lemma Uitgevers. Wilson, R.A. & Sangster, A. (1992). The automation of accounting practice. Journal of Information Technology. 1992;7;2: 65 – 75, https://search.proquest.com/abicomplete/docview/901467535/B15A7CFBCE7841F3PQ/3?accountid=11077 Wohlner, R. (n.d.). Accounting Basics: Branches of Accounting. Investopedia, https://www.investopedia.com/university/accounting/accounting2.asp Zarowin, S. (1994, March). CPA 2000: What's ahead for accounting software. Journal of Accountancy. 1994;177;3: 54 – 58, https://search.proquest.com/abicomplete/docview/206732282/5041E8AB8B2146F4PQ/1?accountid=11077

77

Annexes 1. Printscreen databases

a. ABI/INFORM Collection

b. Accounting, Tax and Banking Collection

c. Web of Science

2. Overview selected articles

3. Interview guideline

4. Confidentiality agreement

78

Annex 1: Printscreen databases a. ABI/INFORM Collection

b. Accounting, Tax and Banking Collection

79

c. Web of Science

80

Annex 2: Overview selected articles Author Title Year Country Study objective Method Findings

Al-Htaybat et al. Big Data and corporate reporting: impacts and paradoxes

2017 United Kingdom The purpose of this paper is to investigate the phenomenon of Big Data and corporate reporting, and to determine the impact of Big Data and the current Big Data state of mind with regard to corporate reporting, what accountant and non-accountant respondents’ perceptions are of the phenomenon, what the accountants’ role is and will be in this regard, and what opportunities and risks are associated with Big Data and corporate reporting. Furthermore, this study seeks to identify the inherent technological paradoxes of Big Data and corporate reporting.

Interview Three topics, or categories, emerged from the data analysis, which have sufficient explanatory power to illustrate the phenomenon of Big Data and corporate reporting, namely the Big Data state of mind and corporate reporting, accountants’ role and future related to Big Data, and perceived opportunities and risks of Big Data. Features of a new approach to corporate reporting were identified and discussed. Furthermore, four paradoxes emerged to express inherent opposing positions of Big Data and corporate reporting, namely empowerment vs enslavement, fulfilling vs creating needs, reliability vs timeliness and simplicity vs complexity.

Anonymous Expert Systems for Accountants: Has Their Time Come?

1987 United States The paper identifies the benefits of automation.

Literature review

The benefits from using expert systems to perform these tasks include: 1. the preservation and distribution of expertise, 2. the improvement of personnel productivity, 3. The enhancement of quality control, 4. the facilitation of education, and 5. the facilitation of complex analyses. Potential accounting applications of Expert Systems include: 1. audit and tax planning, 2. internal control and accounts attribute analyses, 3. quality reviews, 4. decision making, 5. management consulting, and 6. training.

Arntz et al. Revisiting the risk of automation 2017 Netherlands Various empirical assessments suggest that up to half of all jobs in western industrialized countries are at risk of automation in the next 10 to 20 years. This paper demonstrates that these scenarios are overestimating the share of automatable jobs by neglecting the substantial heterogeneity of tasks within occupations as well as the adaptability of jobs in the digital transformation.

Quantitative research

The study reveals a serious and systematic upward bias in occupation-level estimates of automation potentials compared to a job-level approach, as workers specialize in non-automatable niches within their profession. The automation risk of US jobs drops from 38% to 9% when allowing for workplace heterogeneity. 38% of the workers perform jobs with a risk of automation above 70%.

81

Baldwin et al. Opportunities for artificial intelligence: Development in the accounting domain: the case for auditing

2006 United States This paper reviews the nature of accounting and auditing problems and the need for application of Artificial Intelligence (AI) technologies to the discipline.

Literature review

A number of types of decision-making theory and AI technology have been applied to auditing and assurance problems. Not all applications of AI to audit problems have proven successful in the long run. Abdolmohammadi (1991) studied 332 tasks that auditors perform. Although the number of potential tasks is high, not all are suitable for AI application. Some are very structured and fairly routine, such as computation of inventory ratios. Others are much less structured and rely on uncertain and incomplete information, such as a going-concern determination. Research on AI for these tasks will be improved if accounting researchers and AI researchers across disciplinary lines and work together. Furthermore, most of the AI research in auditing and accounting has involved expert system technology. Clearly, more complex AI applications can be created to solve some auditing problems more fully. Audit tasks, such as analytical review procedures, materiality assessments, going-concern decisions and risk assessment, are complex and important. Performing these tasks poorly has dire consequences (e.g. Arthur Andersen). The potential for improvement through the development and use of complex AI applications, such as expert systems, genetic programming, neural networks, fuzzy systems and hybrid systems, should be investigated to the fullest extent possible.

Beaman et al. Information Technology, Decision Support and Management Accounting Roles

2007 United States The paper investigates the possibility that accounting functions within organisations are becoming restricted to the areas of financial reporting and transactions processing, rather than decision support and problem solving.

Two surveys The findings of both studies show that management accountants perceive they spend on average only a third of their time on the latter types of management accounting activities. The paper also identifies the specific IT skills necessary for decision support systems and discusses how such skills should be incorporated in accounting education programs.

Blum, Albert A. Job skills for automated industry 1986 United States The paper studies the required skills for automated industry.

Literature review

Present employees tend to lack “basic qualifications”, and that the schools have to provide them, as well as provide retraining for the adults. Companies will not retrain employees who do not have adequate basic training. Employers are often requiring a high school diploma for jobs that formerly did not require it, and those jobs that require more education are increasing faster in our labour market than those, which require less education.

82

Chase et al. Artificial Intelligence and Big Six

Accounting 1991 United States This article studies

the use of Artificial Intelligence in the form of Expert Systems in large accounting firms.

Literature review

In the future the number of experts systems will increase heavily. To survive to this new technology, expert systems will not be only used by big accounting firms, but by small companies as well. Public accounting is an activity that lends itself to the application of AI technology. It seems clear that AI will be integrated into the daily operations not only by the larger firms but of all public accounting firms that wish to maintain a competitive advantage in the twenty-first century.

Chelliah Will artificial intelligence usurp white collar jobs?

2017 United Kingdom In view of recent advances in Artificial Intelligence (AI), has the time arrived for the demise of white collar jobs and how does this change the shape of the workforce, and HR’s role in managing it?

Literature review

The humans are clearly in competition with AI. Since 1950 the increase in investments in capital dropped the employment in manufacturing. However, it increased the jobs in services from 50% to 70%. The employees will have to work with machines and the white-collar jobs might be replaced by AI.

Cole, R. C. Jr. & Hales, H. L.

How Monsanto justified Automation

1992 United States The paper identifies the keys to success in automation.

Case study Develop an overall vision of the future – a long term plan – and justify the entire plan as a whole; Analyse and define the key cost drivers at each step of the production process; Implement measurement techniques to track improvements and their impact on operations; and Concentrate on overall process and quality improvement, not just direct labour savings.

Coyne, J. G., Coyne, E. M. & Walker K. B.

Accountants and Tech : A game changer

2017 United States The paper studies the skills that accountants will need to be able to work with automation.

Literature review

Because employers have begun to demand new skills of accountants, professional organizations like IMA® (Institute of Management Accountants) should continue to encourage and work with the university community to re-evaluate the current model for accounting information systems and the encompassing curriculum to determine what revisions are necessary to train accountants. Additionally, we suggest exposing students to enterprise-grade operating systems (Unix and Linux) and database management systems (Oracle, MySQL, Apache Cassandra). Because of an increase in in-house software development, we also propose that students learn about opensource software and current software development methodologies, especially DevOps.

83

David H. Why are there still so many jobs? The history and future of workplace automation

2015 United States The paper investigates the impact of automation and new technology on middle class jobs.

Literature review

While some of the tasks in many current middle-skill jobs are susceptible to automation, many middle-skill jobs will continue to demand a mixture of tasks from across the skill spectrum. For example, medical support occupations radiology technicians, phlebotomists, nurse technicians, and others—are a significant and rapidly growing category of relatively well remunerated, middle-skill employment. Significant stratum of middle-skill jobs combining specific vocational skills with foundational middle-skills levels of literacy, numeracy, adaptability, problem solving, and common sense will persist in coming decades. The issue is not that middle-class workers are doomed by automation and technology, but instead that human capital investment must be at the heart of any long-term strategy for producing skills that are complemented by rather than substituted for by technological change.

Frey et al.

The future of employment: How susceptible are jobs to computerisation?

2013

United States

The article examines how susceptible jobs are to computerisation. To assess this, we begin by implementing a novel methodology to estimate the probability of computerisation for 702 detailed occupations, using a Gaussian process classifier.

Quantitative research

47 percent of total US employment is at risk. The wave of automation will be followed by a subsequent slowdown in computers for labour substitution, due to persisting inhibiting engineering bottlenecks to computerisation. even with recent technological developments, allowing for more sophisticated pattern recognition, human labour will still have a comparative advantage in tasks requiring more complex perception and manipulation. Yet with incremental technological improvements, the comparative advantage of human labour in perception and manipulation tasks could eventually diminish.

Gamage Big Data: are accounting educators ready?

2016 Australia This paper explores the latest developments in Big Data and its impact on accounting education. As such, it reviews Big Data developments with specific reference to the accounting profession. It also presents some of the initiatives taken by the professional accounting bodies and universities to address Big Data topics in the accounting curriculum.

Literature review

The findings suggest that Big Data will have an impact on the future role of accounting professionals. Therefore, this study proposes that Big Data topics be embedded in existing courses across accounting curricula to prepare twenty-first-century accounting professionals with skills related to Big Data analytics.

Gonzalez et al. Factors Influencing the Planned Adoption of Continuous Monitoring Technology

2012 United States

The authors are interested in the general adoption of the technology, whether by management or auditors, and therefore make no distinction in this regard.

Survey The authors' findings indicate that practitioners who can convincingly harness or communicate social influence, champion the effort, and enhance the perception of the technology's efficacy with a perception that facilitating conditions exist, will build more support for CM.

84

Henry et al. A Survey of Perspectives on the Future of the Accounting Profession

2015 United States

The authors studies differing prognostications on the state and direction of the accounting profession.

Literature review

Accountants will be expected to serve as advisors and participate more in decision-making. Accountants will pursue more education and specialization as firms seek more ways to evaluate the qualification of workers. Firms will continue to struggle to recruit and retain staff, who will opt for more flexible and transient work arrangements. Firms will seek to develop practice niches, such as forensic accounting, to increase profit margins; this may lead to further consolidation. Competition to provide accounting services will increase from outside of traditional providers. Despite the many expected changes, trust will remain the hallmark of the accounting profession.

Herbert et al. The future of professional work: will you be replaced, or will you be sitting next to a robot?

2016 United Kingdom This article explores the often overlapping concepts of work automation and robotic technology before considering the possibilities for transforming the way professional work might be carried out in future.

Interview For management accountants, there is a risk that many present jobs will be eliminated unless they can create new ways of leveraging the new data rich environment that is rapidly enabling a new approach to management information control and decision-making.

Kim et al. The rise of technological unemployment and its implications on the future macroeconomic landscape

2017 United Kingdom

This paper aims to track the relative quantities of jobs that are either susceptible or non-susceptible to computerization in the future.

Quantitative research

Technological progress in recent years has negatively affected employment to a greater degree than ever before. Government intervention and policy changes could help to reduce the impact of technological advancement and an appreciable proportion of total future employment will consist of new occupations that will provide employment opportunities for humans.

Kokina et al. The Emergence of Artificial Intelligence: How Automation is changing Auditing

2017

United States This paper is motivated by the need to explore deeply the use of Artificial Intelligence in accounting.

Literature review

Senior accountants in large firms uniformly argue that the need for human accountants will not go away anytime soon. But many argue that the skills for successful accounting and auditing are likely to be different in the future, and some admit that they will need substantially fewer entry-level accountants in coming years. At least over the next couple of decades, accounting is one of the many business fields that is likely to be augmented by technology rather than fully automated.

85

Liu et al. Big Questions in AIS Research:

Measurement, Information Processing, Data Analysis, and Reporting

2014 United States This editorial poses and explores big questions that emerge from the five aforementioned attributes of accounting.

Literature review

The locus and method of data capture, variables being collected, analytic information being incorporated, and frequency of reporting will undergo paradigmatic change, thus altering the method of business measurement. The pace and adoption of these changes in external reporting is unpredictable due, primarily, to the rigidity of regulatory mechanisms and the strong aversion to usable accountability and disclosure by organizations. The application of sophisticated data analysis technologies will bring great efficiency and support to accounting work, and render some traditional procedures obsolete. Accountants will be able to expand service scope from financial to nonfinancial process measurement by using emerging data analysis technologies. The implementation of exploratory and predictive data analysis approaches will bring fundamental changes to the work of the accountant as well. Reporting will change by benefiting from big data, machine-to-machine communications, emerging analytic tools, and an increasing symbiosis between man and machine.

Marcello et al. The Future of Auditing: A roundtable discussion

2017 United States This paper examines the state of the auditing profession. Has the profession met the expectations of the user community? How will technology transform the practice of auditing? What skills will future auditors need, and how will tomorrow's auditors be trained, selected, and prepared for the profession?

Interview One of the professionals from the roundtable discussion believes that accountants and auditors need to be careful when using Artificial Intelligence. According to this respondent, human intelligence exceeds machine learning. The professional is sceptical about the use of Artificial Intelligence and does not trust machine learning concerning the decision-making

Moudud-Ul-Huq, Syed The Role of Artificial Intelligence in the Development of Accounting Systems: A Review

2014 The study analyses the relative impact of AI on two different types of accounting works—auditing and tax. Accounting tasks involve a wide range of structured, semi-structured and unstructured decisions.

Literature review

The discussion indicates an impact on factors that ultimately improve productivity. In aggregate, it indicates that expert systems are found to allow the user substantial control of search for solutions and discretion on whether to follow system recommendations, increased access to top management, and a decrease in the need for supervision.

Omar Artificial decision-making and artificial ethics: A management concern

1993 Netherlands This papers addresses three basic reasons for ethical concern when using the currently available expert systems in a decision-making capacity.

Literature review

Since expert systems with artificial ethics are not a fact of life, the responsibility for decision-making should not be completely abdicated to expert systems. Managers should not abandon their responsibility for evaluating and rejecting the advice or conclusion of expert systems.

Oschinski et al.

Future Shock? The Impact of Automation on Canada’s Labour Market

2017

Canada

This article assesses the impact of technological change on Canada’s labour market over the past 30 years and

Literature review

No evidence of an imminent threat of massive unemployment due to automation was found. The automation of job tasks is part of the natural process of

86

highlights its implications for the near future.

technological innovation and a necessary engine of economic growth. Labour market trends show a gradual shift in the skills level demanded, but new technology does not simply make people redundant; rather, it reduces the labour required for a given level of production. This means that more of the same goods can be produced or people can be redeployed in areas that otherwise might not have been developed. This process, already underway, can be moderated by policy that encourages collaboration between public and private institutions to ensure workers have the necessary skills for a technologically uncertain future. Those whose qualifications are no longer in demand should be helped to gain the qualifications they need for new employment.

Özdoğan The Future of Accounting Profession in an Era of Start-Ups

2017 United Kingdom

The predictions of the future of the accounting profession are shared by taking into account the technologies that are being used in today, reflections of these into business and effects on the accounting sector.

Two surveys It has been predicted that technology-based accounting start-ups with both accounting professionals and entrepreneurs having an expertise on information technologies will come together and will increase in the future, and cloud-based accounting initiatives will shape the future of the profession.

Parham et al. Accounting majors’ perceptions of future career skills: an exploratory analysis

2012 United States This study examines the opinions of 205 students to determine what skills they deem to be important for their future careers. The study then compares the opinions of accounting students against other business disciplines.

Survey The results of the study are mixed for the accounting profession. Many of the skills accounting majors ranked as important for their future were not surprising. However, there was some indication that accounting majors may be suffering from a “silo effect” and are not able to fully grasp how skills learned in other university courses impact their professional success.

Rattunde, E. S., Segura, J. III & Wallace, S.

Technological change and job polarization: the Wisconsin experience

2016 United States This study examines the impact of automation on the composition of occupational employment for the United States, Wisconsin and Central Wisconsin. Specifically, the paper analyzes how computer-based technologies and robotics have contributed to job polarization by reducing the number of "middle-skilled" jobs while bolstering employment in both low-and-high skilled jobs.

Literature review

The current pace and scope of technological change implies a need for workers at all skill levels to update their skills throughout their working years. Unfortunately, the United States badly trails other developed economies in providing opportunities for job retraining. As the capabilities of machines encroach on more abstract tasks, higher-skilled workers may find the need to update their skills as well.

87

Sangster, A. The adoption of IT in management accounting: the expert systems experience

1994 United Kingdom This article considers why, despite forecasts to the contrary and in spite of being apparently well-suited to the technology, management accounting-based expert system developments appear to be virtually non-existent.

Survey The findings suggest that management accountants may lack both awareness of the term and understanding of the nature of expert systems and that they generally do not believe that software can be trusted to make their job easier and improve the consistency of their decision-making. It is concluded that a major educational initiative may be required if there is to be any likelihood of a significant change from the current position.

Silverman, W. The Economic and Social Effects of Automation in an Organization

1966 United States The paper studies the economic and social effects of automation.

Literature review & Case study

Automation usually reduces employment in organizations in which it is introduced. The number of jobs that are lost depends on the demand for the product or service produced by the organization. The people who are most likely to lose their jobs are young female clerks. Automation destroys old skills but at the same time creates new skills requiring operation of the more complex machinery. Automation has both favourable and unfavourable effects on jobs quality.

Sorgner, A. The Automation of Jobs: A Threat for Employment or a Source of New Entrepreneurial Opportunities?

2017 Russia This paper investigates the relationship between the risk posed by the automation of jobs and individual-level occupational mobility. It provides an overview of current trends and developments on the labour markets due to the automation of jobs. It also describes the most recent dynamics of self-employment and relates it to the risk of the automation of jobs.

Survey The results suggest that the expected occupational changes such as losing a job, demotion at one’s current place of employment, or starting a job in a new field are likely to be driven by the high occupation-specific risk of automation. However, the switch to self-employment, both with and without employees, is more likely to occur from paid employment in occupations with a low risk of automation. Hence, the rising level of entrepreneurial activities is less likely due to jobs becoming obsolete over the course of automation, but rather due to the high number of opportunities offered by the digital age.

Tuzhilin IT-Driven Automation: The Next Wave

2004 United States This article claims that the next waive of automation will affect not only routine production workers, but also what Reich calls symbolic-analytic workers.

Survey Jobs including repeated, stabile and structured tasks, have been reduced dramatically since many years. This article argued that technology will be developed and have a significant impact in the economy in the next 10-15 years. The improvement in technology will have a positive effect leading to an increase in productivity and more job satisfaction. In another hand, the labour market will change and needs to be managed properly. The political and social issue should be solved before the automation affects the market.

Wilson et al. The automation of accounting practice

1992 United Kingdom

This article examines the use of computer technology by the UK accounting profession and why the accounting profession should be aware about automation.

Survey The results also show that computer use differs from working environment but not from organizational size. The development of the software will obviously increase the automation of the accounting and could have a big impact on the accounting profession.

88

Zarowin CPA 2000: What's ahead for accounting software

1994 United States

The purpose of this article is to study the impact of the computer revolution in the accounting profession.

Interview Most CPAs use computers simply to automate routine tasks. That’s about to change, and the accounting profession is about is about to change too. The change that will affect accountants immediately is increased user-friendliness. The Software of the future will have more than context-sensitive help screens; will have built-in voice and video aids. Most of tomorrow’s software will be designed to follow the user’s logic and intuitiveness. Because computers will be easier to use, accountants will find them more effective. Accountants shouldn’t worry that computers will make them obsolete. Computer can’t think, they can’t perform accountants’ most valuable functions: interpreting and analysing financial information, legal developments or marketing trends and presenting the analyses to the decision makers.

89

Annex 3: Interview guideline General questions

• What is your current job title?

• Since how long do you work in the company?

• Since how long do you work as an accountant?

Questions about automation • Do you use automation in your company?

o If so, for how long is automation being used in your company?

• Did you receive training in working with automation? o If so, how did that training look like o If not, do you think it would have been helpful/necessary and how would

that training would have looked like?

• For which tasks do you use automation? And why?

• What are the main reasons for using automation?

• Which tasks do you believe are more difficult to automate?

• Is it a realistic prediction to say that automation will compliment employees in their work tasks rather than replace them entirely? If so why or why not?

• Do you believe the accounting industry is more likely to have technological

unemployment than any other industry?

• In your opinion, what will be the implications of automation in the accounting profession for the future?

• What do you believe is the main limitation of automation?

Qualitative characteristics

• Do you think that automation can provide useful financial information required by the qualitative characteristics of the Conceptual framework? (relevant, represented faithfully, comparable, verifiable, timely and understandable)

• Which aspects of the qualitative characteristics do you think automation

can do better? (than human intelligence) and which characteristics can automation not do better?

• Do you believe that automation reduces the risk of errors?

90

Skills of the accountant • What skills do you believe the accountant possesses that cannot be done

by automation? o Why?

• Do you think accountant will have to develop their skills to remain

important? o If so, what skills need to be more developed?

• What are your thoughts on changing university courses so that accounting

students learn to work with automation? o In your opinion, to what extent does automation needs to be taught at

university? Small accounting firms

• Do you think small companies are more likely to technological unemployment?

• • Do you think small accounting firms will have difficulties to remain

competitive due to the high investing cost of automation? o If so, what can they do about this?

91

Annex 4: Confidentiality agreement PERMISSION I declare that the content of this Master’s Dissertation may be consulted and/or reproduced, provided that the source is referenced. Name student: Mélanie Simon Signature: