The Ladder to AIJanine SneedChief Digital OfficerVP of Customer Success

IBM Cloud and Cognitive Software

Each of us makes35,000 decisions a day

IBM Analytics / © 2018 IBM Corporation2

IBM Analytics / © 2018 IBM Corporation3

Some decisions are challenging

IBM Cloud / © 2018 IBM Corporation4

Others are regrettable…

IBM Analytics / © 2018 IBM Corporation5

Each day…Awake for 16 hours a day…

Make 2,188 decisions every hour

Work for 8 hours a day…

Make 17,500 decisions at work each day

That’s 36 decisions per minute

If Then If Then

What if we seek out and automate boring decisions?

IBM Analytics / © 2018 IBM Corporation6

“If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.”

- Andrew Ng, Former Chief Scientist of Baidu (2016)

7 IBM Analytics / © 2018 IBM Corporation

AI is anything a computer can do that feels like MAGIC today

8IBM Analytics / © 2018 IBM Corporation

IBM Analytics / JLG / June 2018 / © 2018 IBM Corporation9

IBM Cloud / © 2018 IBM Corporation10

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Data Driven Insight Driven Digital Transformation

Discover “what”Understand “why”

ReportsBusiness Intelligence

Data Warehouse

Cost ReductionModernization

PredictionOptimization

ModelsVisualizationApplications

New Business ModelsReal-Time Decisions

AIMulti-Cloud

Outcomes

Capabilities

Drivers

How do you get there?Most are here

Competitive MarketLeader

Value from Data

Why are many businesses not further along?

� Disparate data types

� Various data sources

� Data silos

� Data quality challenges

� Data accuracy

� Talent shortage

� Growing external risks and compliance mandates

81% do not yet understand the data required for AI- MIT Sloan, Reshaping Business With Artificial Intelligence, September 6, 2017

COLLECT - Make data simple and accessible

ORGANIZE - Create a trusted analytics foundation

ANALYZE - Scale insights with AI everywhere

Data of every type, regardless of where it lives

MODERNIZEyour data estate for an

AI and multicloud world

INFUSE – Operationalize AI with trust and transparency

The AI LadderA prescriptive, proven approach to accelerating the journey to AI

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AI

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Freedom of self-service, data migration and scalability

Common SQL engine: write once, run anywhere

Big Data , IOT data, and data warehousing

Embedded machine learning and analytics

All data types and workloads

Hybrid Data Management

Collect DataMake data simple and accessible

Built-in data virtualization

Deployed a high performance data warehouse on hybrid cloud to fuel audience preference analysis

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Unified Governance

& IntegrationManage fluid data with protection

and compliance (e.g., GDPR)

Profile, cleanse, integrate and catalog all types of data

Embedded machine learning automation

Persona-based experiences with built-in industry models

Govern data lakes and data warehousing offloading

Policy and business driven visibility, discovery and reporting

Organize DataCreate a trusted, business-ready analytics foundation

New Jersey CourtsNew predictive system built upon real time state/federal crime data repositories and a complex business rules driven architecture

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Data Science & AI

Deployed machine learning to predict fraudulent activity across their web & mobile banking system, reducing the high “false positive” rates of past systems

Predictive & prescriptive modeling, data mining and statistical analysis

Design, build and train data science and AI models

Automates model deployment and business process integration

Dynamic planning, budgeting and forecasting analytics

AI-assisted business intelligence and dashboarding

Deploy, run and retrain AI & ML models anywhere

Analyze DataScale insights on demand with AI everywhere

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OperationalizeAI

Infuse AIOperationalize AI with trust and transparency

Full transparency with explainability and bias mitigation

Automated fairness and issue detection

Decision auditability, traceability and accuracy analytics

Ensure responsible use of AI and predictability for their tax,

audit & advisory services.

Deploy intelligent AI model management workflows

Automates the design and deployment of neural networks

Integrate AI models into process automation platforms

Deployed Cora, an AI assistant to help RBS clients gain new

insights and answer questions.

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The Ladder to AI

IBM Data & AI PortfolioEverything you need for Enterprise AI, on any cloud

WatsonStudio

Watson Machine Learning

Watson OpenScale

Build Run Manage

Pre-built Use CasesWatson Applications

Multicloud Data & AI PlatformIBM Cloud Private for Data

Hybrid Data ManagementDb2 Family

Data Governance & IntegrationInfoSphere FamilyOpen source meets a

multicloud, working as ONE

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UNIQUE CHALLENGE

Getting LOB aligned

Access to data silos

Different data types

Standardizing on common terms

EXPECTED BENEFIT

Consume and use data with confidence

Clarity and trust: where the data resides, what the data means, who owns, how it’s used

Governed foundation to make changes fasterScale

USE CASE

Use case

Large bank had a complex landscape that grew through acquisitions, legacy development, and shadow IT. They needed a trusted architecture that all 55,000 employees could access self service for projects. After setting up a CDO, they worked with all lines of business to introduce a fully governed data lake, instantiate a corporate language, and enable data scientists to build machine learning prediction models.

Bank democratizes data empowering 55,000 employees with trusted, accessible data -at scale

Best in Class: Democratizing data for self service empowerment at scale

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UNIQUE CHALLENGE

Legacy

Identify data across 300 apps

Map out sensitive data elements

Common enterprise vocabulary that everyone could use

EXPECTED BENEFIT

New culture /thinking

New insights to LOB while protecting customer personal data Faster decision making

Consistent, trusted data

USE CASE

Use case

A large wealth and asset management company always paid a lot of attention to data governance and analytics but with GDPR, they saw an opportunity to go beyond compliance while bolstering its data governance strategy and insights for more informed decisions. They established an enterprise data program putting policies and processes in place for identifying, governing, and managing access to personal information.

Wealth and Asset Management company unlocks data with visibility and control

Best in Class: Democratizing data for while adhering to GDPR

“With good quality data with embedded governance controls, my group is providing better service to my constituents so Northern Trust can better serve its customers.” - Sanjay Saxena – SVP of Enterprise Data Governance, Northern Trust

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UNIQUE CHALLENGE

Many acquisitions

Extremely slow web response times

Record of customer interactions

EXPECTED BENEFIT

Customer Loyalty

Amazing, seamless experience across multiple brands and channels10X Faster Response time on the mobile app

Improved, accurate, trusted customer data

USE CASE

Use case

A US retailer prides itself on the customer experience. With acquisitions of many brands, it was important to enable users to move across multiple sites and loyalty programs. Managing a single view of the customer data (web interaction, card payments, purchase history) was problematic, ridden with security challenges, and was extremely slow. They overhauled their MDM solution managing 70M customer records and delivered an improved mobile app with 100 MS response time.

A large retailer improves customer experience and loyalty with seamless cross channel and brand UX

Case Study: Democratizing data for Customer UX and 360 Customer View

2323

Enriched interactions between clients and advisors by empowering advisors with information to quickly serve customers

Case Study: Democratizing data for customer – agent interactions

UNIQUE CHALLENGE

Culture: Jobs

Scale

Data Volume

EXPECTED BENEFIT

• Find answers for employees 60% faster

• 50% savings in analyzing emails

• Deflects and addresses 50% of the 350,000 daily emails received by the bank’s client advisors

USE CASE

Global Bank has over 5,000 branches with more than 350,000 emails each day – growing 23% YTY. Client advisors were spending their time answering simple and repetitive questions. With the help of an email analyzer and a virtual assistant, common questions were automate across savings, credit, and insurance. Now more than 35,000 employees strengthen their customer relationships by answering questions 60% faster.

2424

IBM empowers it’s marketing and offering managers with self service analytics to understand and optimize campaigns and offerings

Case Study: Democratizing data for campaign and offering insights

UNIQUE CHALLENGE

Data Silos

Disparate Data

Skills

Complexity

EXPECTED BENEFIT

• Real time insight

• Single source of truth

USE CASE

IBM wanted to provide real time insight, 24x7 to marketing and offering professionals on how their products and campaigns were performing. Sponsored by the CMO and CDO, they created a performance marketing organization to lead the charge and build the platform. The solution integrates 16 different data sources, provides real time self service insights, and is MVPing revenue projection models.

2025