beyond rpa: impact of ai for end- user application ... · current state journey intelligent...

Beyond RPA: Impact of AI for End-User Application & Device Support

Sam Gross, Founder & CEO, ChoiceWORX

2SIMPLIFYING THE INTELLIGENT AUTOMATION OF IT Confidential

Definitions:RPA Automation vs. Intelligent AutomationRPA Automation - Smart software programmed to do high-volume, repeatable tasks

2

…gives any work process that is definable, repeatable and rules-based the ability to map out a business process and assign a software robot to manage the execution of that process

Designed to be a proxy for a human worker

…ability to analyze vast amounts of dynamic and unstructured input and execute processes that are highly dynamic and non-rules based.

Learning systems that are adaptive and can make adjustments optimized for a new situation

Intelligent Automation - Systems that Think, Systems that Learn, Systems that Adapt

3CONFIDENTIAL

Cost?Time?

Expertise?Risk?

Software Platform

Fit forPurpose

General Purpose

Definitions:Fit for Purpose Platforms vs. General Purpose Software

4SIMPLIFYING THE INTELLIGENT AUTOMATION OF IT CONFIDENTIAL

Digital Disruption:Requires Legacy IT Paradigms to Change Dramatically

THE GAP

FUNCTION-BASED TOOLS/CONSOLES OPEN, API ENABLED, DIGITAL PLATFORM

SITUATIONAL, SELECTABLE, & ALGORITHMIC FLOWS

Policy

Preference

Cost

Expedience

First

COIN-SORTER FIFO STACK

BOTS, OMNI-Channel, DIGITAL L1ARBITRAGE, SPECIALIZED, REPETITIVEService Desk DesksideNOC/Ops

TRADITIONAL OPERATIONS PARADIGM

IT as Integrator/Sourcing Specialist

DIGITAL OPERATIONS PARADIGMIT as Digital Enabler

LABOR DYNAMICS

PROCESS DYNAMICS

TOOLS DYNAMICS


Digital Disruption: Legacy Analog Support ProcessesWill NOT support your Digital Transformation

Current State Journey

Intelligent Automation Journey

How it starts Digital data from device is transformed into analog message by the End-user and relayed to the call center

Analog message from End-user is transformed into digital data by the call center agent and entered into a case management system

HUMAN SpeedEffort: 15 Min – 4 Hrs.

Digital fault data from device is delivered directly to the AI Automation

A BOT and AI in the cloud pinpoint the causal fault, orchestrate remediation and validate an operational state . Symptomatic faults are ignored because the context of the application is fully evaluated

MACHINE SpeedEffort: 30 Sec to 5 Min

End-user application or device fails and generates digital data on End-user device

15 Min

Expedience

30 Sec

Expedience

4 Hrs

5 Min

Effectiveness

Effectiveness

SME diagnoses the issue by asking question of the End-user or initiating a manual remote control session on the device


Digital Disruption: Impacts your IT InfrastructureAt the Same Time as Your Applications

DATA CENTER AUTOMATION

ORIGIN

▪ JCL

▪ Scheduling

▪ Scripting

▪ Runbook Automation

▪ OEM Consoles

DESTINATION

ARTIFICIAL

INTELLIGENCE (AI)

ENABLED & DRIVEN BY:

NEXUS OFFORCES

EXPERIENCEECONOMY

DIGITAL TRANSFORMATION

FOUR INTERDEPENDENT PATHS OF EVOLUTION

BUSINESS PROCESS AUTOMATION

Trigger-based, Stored Procedures

INFRASTRUCTUREIMPACTS ANDEVOLUTION

TECHNOLOGYAUTOMATIONPROGRESSION

DATA REPRESENTATIONCONTINUUM

Rules-based, Structured Workflows

Robotic Processes, Natural Language

OrchestrationRobotic Process

AutomationNarrow AI

Self-learning

Structured & Managed Master

Data ManagementBig Data,

UnstructuredGraph Data,Self-defining

Flow-based, Policy enabled

Cognitive Computing

Adapted from HfS, Gartner, IRPA

Ad HocITIL

COBIT Lean ITBi-ModalDevOps

Modern Service Management


Digital Disruption: Industrialize RPA with an AI platform When your RPA BOT Fails…… HOW WILL IT GET FIXED?

End-point Device

Operating Environment

Database Server

Application Server

Network

Browser / Client Software

Web Server

Browser / Client Software

Database Server

Application Server

Web Server

Appl

icatio

n 1 Application 2RPA BOT

What Failed?


Digital Disruption: Industrialize RPA with an AI platform

� MACHINE LEARNING─ identifies patterns within data sets and tries to make predictions based on existing data─ Needs a large volume of data to learn and be able to find valuable information in patterns ─ Plausibility and correctness of results is important, it is usually possible to find something in large sets of data. ─ Not useful in situations where there’s no data, other than some initial conditions, and constraints

� COGNITIVE COMPUTING─ Handles conceptual/symbolic data rather than just pure data or sensor streams─ Computing that comprehends at an advanced level─ Facilitates human intelligence─ Humans are firmly in charge of decision making

� MACHINE REASONING─ Generate conclusions from available knowledge by using logical techniques such as deduction and induction. ─ Reasoning systems interact with Semantic Graphs providing expressive power and predictive abilities─ Algebraically manipulates previously acquired knowledge in order to answer a new question─ Uses algorithms to replicate human actions and self-determines the Next Best Action

Platforms for Machine learning, Cognitive computing, Machine reasoning, Sematic analysis, Deep learning & Natural language processing are important to understand


OBJECTIVE Reduce the time to get what is wanted or required.

MEASUREMENTTotal time to complete the ask with active & wait values

EXPEDIENCE EFFICIENCY

OBJECTIVEReduce the total cost of operations or ownership.

MEASUREMENT Total cost/flow to complete by skill mix & choice.

OBJECTIVEIncrease successful outcomes & process consistency.

MEASUREMENTTrack satisfaction, successful outcomes & process consistency.

EFFECTIVENESS

OBJECTIVEReduce the number of touches, redirects & resupplies of information.

MEASUREMENTCount total touches, redirects & restarts per issue.

EMPOWERMENT

OBJECTIVE Anticipate & supply guidance for next steps & actions to success.

MEASUREMENTClick-through percent on recommendations & automation success.

ENRICHMENT

Digital Disruption: Boost Customer and Employee SatisfactionReimagine Metrics When Powered by an AI Platform

Traditional IT Service Level Measurements Have Become Obsolete


Digital Disruption: ApptinuumReimagine End-user Application Support & Device Support

Solve Recurring IT problems Before You're Even Aware of ThemProactive & Instantaneous Remediation and ChatBOT Powered End-user Support Improve Application

Availability

Boost End-user Experience AND Reduce Cost

Complicated Scripting and Agents Are No Longer Necessary

Full Service Automation as a ServiceBenefit from AI without Hiring or Re-skilling


Digital Disruption: Apptinuum and Intel vPro AMT

Provision

Manage

RemediateSecure

Break/Fix

Firmware UpdateAgent Presence

DiscoveryRemote Command

System Defense

Platforms equipped with Intel vPro AMT

can be managed remotely,

regardless of whether they are

powered up or whether they have

a functioning OS

HardwareEvent Manager

Fast Call for HelpKVM

Extended functionality to Robotically Enable an End-point Device across the lifecycle is delivered to the chip by Intel vPro Active Management Technology


Enjoy Significant Labor Cost Reduction…AND Boost End-user ExperienceThe first specialized SaaS Automation as a Service platform combining AI and Intel vPro Active Management Technology (AMT) for automated End-user Application and Device Support

13CONFIDENTIAL

To Learn MoreVisit OUR Exhibit

Sam [email protected]

www.ChoiceWORX.com

Thank you for joiningBeyond RPA: Impact of AI for End-User

Application & Device Support

mailto:[email protected]

beyond rpa: impact of ai for end- user application ... · current state journey intelligent...

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