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Magnus Revang

Research Vice President

Gartner

Hvordan Benytte AI for å fremme vekst i virksomheten

1 © 2018 Gartner, Inc. and/or its affiliates. All rights reserved.

... the user isan operator

of technology

Paradigm Shift: In Today's Screen-Based Paradigms ...


Technology is an agentfor the user


AI Is a Diverse Set of Technologies and Approaches

Many definitions: Intelligence exhibited by machines, a collection of disciplines and research areas, the search for general intelligence, marketing fog

AI

Deep Learning

Multilayer neural networks

Intermediate representations of the data

Algorithms to parse data, learn from it, and then make a determination or prediction about something in the world

Statistical Machine Learning

Semantic AI

High-level "symbolic" (human-readable) representations of problems, logic and search

Rules & Representations

Machine LearningTraining and Configuration

Time

4 © 2018 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.

You probably think

you’re behind on AI,

but you aren’t.

But CEOs think it’s the

most important

advanced technology.

Few CIOs says they

employ AI today.


25% 21% 4%

Be Patient! You’re Not As Far Behind As You Might Think

Percentage of Respondents

No interest

14%

On the radar, no

action planned

35%

In medium- or long-

term planning

In short-term

planning/actively

experimenting

Have already

invested and

deployed

Q: What are your organization's plans in terms of artificial intelligence?

Base: All Answering, n = 3.138

Source: Gartner 2018 CIO Survey


AI Suggests a Strategy, Because It’s a Long Effort

Base: Answered artificial intelligence (AI) section and in the planning phase, n = 176Q: How long, from your organization’s initial investment to project launch, is this AI project projected to take?Q: And, do you think that your organization will accomplish this AI project, it is projected to take?Base: Answered artificial intelligence (AI) section and in beyond the planning phase, n = 714Q: How long did it take from your organization’s initial investment to when your organization first piloted this AI project?

Plan and Pilot Launch!

3 4

Start Planning! Still Planning …Then a Pilot

Still Piloting Launch Happens!

Years 1 2

How long it really takes

Expected AI project duration


Challenges in Adopting AIWhat’s holding organizations back on AI?

Enterprise maturity

Fear of the unknown Vendor strategy

Finding their starting pointEnterprise maturity

Risks/Liabilities

32%Value measurement

24%

Confusion over

vendor offerings

20%

Governance issues

20%

Understanding

what AI is

20%

Lack staff skills

23%

Finding funding

24%

Integration complexity

33%

Security/Privacy

37%

Strategy definition

30%

Finding use cases

30%

79%

40% 63%

48%

Base: Answered artificial intelligence (AI) section, n = 890

Q: What are the top three challenges to the adoption of artificial intelligence (AI) within your organization?


Risks of AI

Operational risk — Breakdowns in AI-cripple

operations.

Financial risk — Developing reliable AI or fixing

problems costs the enterprise a lot of money.

Information risk — Mistakes with AI cause bad data

to propagate across enterprise systems.

Partner risk — Problems with AI damage

relationships with ecosystem partners.

Privacy risk — Hacks or mismanagement of AI

inadvertently reveals sensitive customer information.

Legal risk — New laws and regulations restrict the AI

business practices or lead to heavy fines.

Brand risk — Mistakes involving AI damages the

reputation of the enterprise and its products.

Geopolitical risk — AI could undermine social,

economic and political structures.

Market risk — AI could fundamentally cripple or alter

the enterprise’s markets.

Communication risk — Public fears about AI make it

difficult for the enterprise to offer positive AI solutions.

9 © 2018 Gartner, Inc. and/or its affiliates. All rights reserved.9 © 2018 Gartner, Inc. and/or its affiliates. All rights reserved.

Deep Neural Network System Model

DNN Training System

Training Data

Model and

WeightsExceptions

Testing Data

Operating Data(Real-Time Video Streams)

Rule-Based System

DNNRuntime

Production

Training

Action


Industry: Government

Use Case: Classifying Patents to the right

highly skilled specialist

Expected Results: Reduction in staffing of

semi-skilled workers doing manual classification

How: Proof of concept project using Azure

Machine Learning, by a single graduate student,

over the course of 4 months

IP Australia – Proof of Concept


Duration: 1 year

Challenges:

– Security and Privacy

– Integration

– Tweaking of the Training Data

Launched in October 2017

IP Australia – from PoC to Production


Expected Result: Reduction in staffing of

semi-skilled workers doing manual

classification

Actual Result: Vastly improved Customer

Experience from Patent Applications being

processed in a much shorter time – seen as a

more important benefit than the cost reduction

IP Australia – the Surprising Result


Three levels of exposure

Frameworks and Algorithms

Build-it Yourself

Hosted AI Services

SaaS through APIs

Products

Software

Need for New and Different Skills

Amount of Exposure


Training

Learning

Performance

AI - 1

AI-2

AI-3

AI-4

AI-5

End users and vendors should view machine

training and learning as different but

complementary activities.

They are often conflated and placed in the hands

of vendors.


Questions we tell Clients to Ask "AI" Vendors

1. What does AI mean to you (the vendor)? How does this product fulfill that definition?

2. How is your product superior to current options that have no AI?

3. Once I have your product installed, how will its performance improve through AI?

4. How should I expect to devote staff and time to such improvements?

5. How can I see that will happen with data that is related to my project?

6. What data and compute requirements will I need to build the models for the solution?

7. What resources are available to gather and refine data that the AI solution can use such that its outcomes improve?


33%22%22%20%18%17%

10%11%8%9%

53%63%62%

59%58%50%

56%53%54%49%

14%15%16%21%23%34%34%37%38%42%

Job securityAmount ofcontact andcollaboration

with co-workers

Amount ofcontact andcollaboration

with customers

Variety of tasksin my job

How interestingmy job is

Pace of work /workload

Quality of work Ideliver

Training anddevelopment

Safety at workMonitoring myactivities at

work

Increase

Stay theSame

Decrease

Employees expect AI to change many aspects of their jobs

Q20. What impact do you think AI will have in the following aspects of your particular job?

Base: Employed, n=2,708

Percentage of Respondents

Expected Impact of AI in jobs


Trust, safety

Attitude to "things" and "intelligence"

Weaker personal relationships

New working practices and skills, deskilling of some roles

Change in field workforce role from "heroes" to "replacers"

Opaque systems and recommendations

Manage the Human Relationship to AI and Robots

Technology

as tool

Technology as a

subordinate

Technology as a

social peer

Customer issues Employee issues:

All projects that deploys AI solutions for automation in the enterprise

will need a change management project running in parallell


Action Plan

Tomorrow Morning:

Demand that Leaders Responsible for Security, Privacy and for Integration will be ready for AI deployments by 1st of December

Next 3 months:

Form a Center of Excellence to run proof-of-concepts opportunistically to learn and build skills

Before the 2019 is over:

Put your first integrated AI project in production with a parallel People Project –become a leader, not a follower

Together with HR, revise HR and hiring strategies for impact of AI

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