AI is transforming every aspect of our daily lives and the data landscape is becoming increasing open and transparent, thanks to the Consumer Data Right, most notably Open Banking. Between the high level academia and low level algorithms, where should the modern business leader start on their AI journey and harness true value from their data? Let us show you a step by step, data-driven approach towards enterprise-wide AI adoption.

1. S U M M I T
SYDNEY

2. A Data-Driven
Roadmap to
Enterprise AI Strategy
Yun Zhi Lin, Head of Engineering at Contino

3. Cloud Platform
Build & Migration
Enterprise DevOps
Transformation
DevSecOps and
Cloud Security
Cloud Native
Software Development
Data Platforms
& Analytics
I’m Yun,
Head of
Engineering.

4. Key Takeaways
01 | Enterprise AI in 2019, Trends & Challenges
02 | Practical steps to drive Enterprise-Wide AI Strategy
03 | Reference Framework for Execution and Scale

5. Enterprise AI in 2019,
Trends and
Challenges
Source: still from Blade Runner 1982

6. Our Definition of Artificial
Intelligence
Using a computer to interpret data and apply
knowledge, logic and understanding.
Hmm learn all
the things!
KNOWLEDGE
DATA

7. We are living the Age of Implementation where
AI is an Equalizer allowing all companies to create
unique Virtuous Cycle and Defensive Data Moats
Better
Product
More Quality Data More Happy Users
V
AWS

8. but Generate Value and form Defensive Businesses
New Product
or CX
More Intelligent
Product or CX
Hyper Automation
& Optimisation
1 2 3
Most AI Use Cases are Grounded & “Non-Exotic”

9. 9
2019 - Enterprise AI Roadblocks

10. Trust my
“gut feel”!
2019 - Enterprise AI Roadblocks
Have more
Strategy!
Execute
without
Strategy!
Analysis
paralysis or
duplicate
initiatives

11. Misaligned
pocket AI
initiatives
Need
more Skills
Unknown
Unknowns!
Experiment!
I have
Bad
Data
2019 - Enterprise AI Roadblocks

12. Patterns?
Automation?
2019 - Enterprise AI Roadblocks
Business
vs IT
Compliance as an
Afterthought? Ethics?
Consumer Data Right?

13. Enterprise AI challenges are not really about
algorithms or technology.
Coherent Strategy Operating Model Execution
The key ingredients of AI adoption are simple:
IT Business
1 2 3

14. Practical steps to drive
Enterprise-Wide
AI Strategy

15. Remember these are our Challenges

16. Need: Align Al Products to Corporate Strategy
Vision
New Product or Service More Intelligence Experience Defensive Data Moat
Corporate Strategy
IT Strategy
Data Strategy Digital Strategy
AI Strategy
Smarter Business
Processes, Maintenance,
WFM and Automation
AI Product 3AI Product 2AI Product 1

17. AI Strategy
Objectives Goals
Tactic 1 Measure 1
Objectives Goals
Tactics Measures
Objectives Goals
Tactics Measures
Tactic 2 Measure 2
Corporate Strategy
Objectives Goals (O KPI)
Tactics Measures (T KPI)
Vision
AI Product 1
Translate & Align Objectives, Goals, Tactics and Measures
AI Product 2

18. Need: Operating Model for Enterprise-Wide AI
Innovation, Collaboration and Consumption
Business IT
AI Product 3AI Product 2
Process
Ethics &
Legal
People
3Cs
Customers
Culture
Comms
AI Product 1
Data Assets
Technology Assets
AI Product 4

19. TACTICS
Products we can build to reach the goals.
MEASURES
Tactics KPIs
OBJECTIVES
Overarching pursuits over the long term
GOALS
Objectives KPIs
PEOPLE ETHICS & LEGAL
Topic: Contributors: Sponsor: Date:
1
2
3
4 5
PROCESSES TECH ASSETS7 86 9
AI STRATEGIC CANVAS
DATA ASSETS

20. ALIGN IT
Objectives &
Goals
PLAN IT
PROVE IT
SCALE IT
IMPROVE IT
Stakeholder
Education
AI Maturity
Assessment
Tactics and
Measures
AI Strategy
Development
MVP Products
(Lighthouses)
AI Community Of
Practice
Improve or
Fail Fast
Continuous
Training
Measures
Validation
AI
Innovation
& Consumption
Model
Consolidate
Artefacts and
Platform
Defensive
AI Asset
Product Driven AI Transformation Road Map
CYCLE OF
SCALING
INNOVATION
AI Business
Case
Revise AI
Strategy
New Product
Features
New MVPs

21. Vision
Alignment
Photo from Contino Exec Data Roundtable
2019
ALIGN IT

22. Telco X Executive Summary
Use of AI to measure Social Sentiment and Fault Prediction
Concierge for increased customer interaction and provide low cost solution for CSR
Rapidly innovate on future Enhancements and Products ideas such as auto fault remediation, workforce management
1
2
3
Current Corporate Strategy Document: 52 pages excluding 400 page appendices
Summary: Telco X is to looking to build AI-driven products to enhance CX and Automation. Long term goal is to prepare
for greater competition due to Consumer Data Right.
Short term is to increase NPS from 70% to 80% for FY20. In order to do this, Telco X thinks the following initiatives are
important:

23. DATA ASSETS
TACTICSOBJECTIVES
AI Driven CX and Automation
GOALS
FY20 NPS Increase 70% → 80%
PEOPLE
Exec Sponsor: CDO
ETHICS & LEGAL
1
2
3
4 5
PROCESSES TECH ASSETS7 86 9
AI STRATEGIC CANVAS AI Driven CXTopic: Head of AIContributors: CDOSponsor:
MEASURES
May 2019Date:

24. Planning
& Assessment
PLAN IT

25. Picking the Right Lighthouse MVP
LargeLow
Low
Small
Long
High
Short
Business
Sponsorship
Duration
Importance
Project Size
Pick this project
Data
Quality

26. Multi Disciplinary AI Squad
Engineers
Data
Scientists
UX
Business SMEs Customers
Site Reliability
Engineer“Brent”

27. ETHICS & LEGAL
MEASURES
TACTICS
DATA ASSETS
OBJECTIVES
AI Driven CX and Automation
GOALS
FY20 NPS Increase 70% → 80%
PEOPLE
Exec Sponsor: CDO
1
2
3
4 5
PROCESSES TECH ASSETS7 86 9
AI STRATEGIC CANVAS AI Driven CXTopic: Head of AIContributors: CDOSponsor:
Categorise
Positive and
Negative
Sentiments
85% Accuracy
over 48 hrs
Network Fault
Prediction MVP
Rank: 1 Size: M
Social Sentiment
Analysis MVP
Rank: 2 Size: S
Chatbot (Later)
Rank: 4 Size: L
May 2019Date:

28. DATA ASSETS
ETHICS & LEGAL
• Privacy and PII
• Opt In Opt out
• 7 Laws of AI (EU)
• Diversity & Bias
MEASURES
TACTICSOBJECTIVES
Predict Faults in advance using Weather and
Network Usage data
GOALS
85% accuracy for predictions
over a 48 hours time frame
PEOPLE
• Exec Sponsor: CDO
• Owner: Head of Operations
• Team: DaVinci AI Squad
• Customers: Castle Hill Beta
Users
1
2
3
4 5
PROCESSES TECH ASSETS7 86 9
AI PRODUCT CANVAS Network Fault PredictionTopic:
IoT Sensor
Data
Ingestion
Weather
Data
Ingestion
Fault
Model
Sensor
(IoT)
BOM
Data
(HTTP)
Fault
Forecast
(Deep
AR)
Legal & Compliance Review
Training
Client Engagement
Communications Strategy
Sales & Marketing Team
CHANGE MANAGEMENT
Ingest
Weather
data per
hour
Ingest
Sensors
data per
min
85%
Accuracy
for 48
hours
May 2019Date:

29. Reference
Framework for
Execution and Scale
PROVE IT SCALE IT IMPROVE IT

30. Treat SageMaker like Cattle! Not Pet!

31. Machine Learning Life Cycle
Product
OGTM
Split Data
Train ModelTest ModelDeploy Model
Monitor and
Validate
AI Problem
Definition
Validation Data Training DataTest DataLive Data
Pretrained
Model / Service
Collect and
Prepare Data

32. Self Service and Automation Patterns
SRE / DevOpsSelf Service and Governance
ML Engineers / Data ScientistsApplication Engineers
Application
Products
SageMaker
Products
Model Notebook
Training
JobAPI Gateway Inference
Lambda
Client
De-Identified Data Lake
Schedule Cleanup
Lambda
Endpoint
Cognito Auth
Encryption
Key
Service
Catalog
Trained
Model
Inference
Image
Deploy
Endpoint
Training
Image

33. MEASURES DATA ASSETS
ETHICS & LEGAL
• Privacy and PII
• Opt In Opt out
• 7 Laws of AI (EU)
OBJECTIVES
AI Driven CX and Automation
GOALS
FY20 NPS Increase 70% → 80%
PEOPLE
• Exec Sponsor: CDO
• AI COP: DaVinci + Tesla
• Customers: Castle Hill
1
2
3
4 5
PROCESSES
• Internal Open Source Policy
• Asset Custodians
• Change Management
TECH ASSETS7 86 9
AI STRATEGIC CANVAS May 2019Date:
Sensors (1min)
BOM (1 hour)
Fault Prediction (24hr)
Sentiments (+ve, -ve)
Categorise
Positive and
Negative
Sentiments
85% Accuracy
for 48hrs
Network Fault
Prediction MVP
Rank: 1 Size: M
Social Sentiment
Analysis MVP
Rank: 2 Size: S
Chatbot (Later)
Rank: 4 Size: L
TACTICS
AI Driven CXTopic: Head of AIContributors: CDOSponsor:

34. Iteratively Scaling AI Enterprise Wide
1
2
3
4 5
Value
Time
Horizon 1
AI Foundations
Lighthouse Initiatives
Plan
Prove Scale
Improve
Align

35. Plan
Prove Scale
Improve
Align
2
3
4
Horizon 2
AI Community of Practice
Assets and Patterns
Wider Initiatives
Iteratively Scaling AI Enterprise Wide
1
2
3
4 5
Value
Time
Horizon 1
AI Foundations
Lighthouse Initiatives

36. Iteratively Scaling AI Enterprise Wide
Value
Time
2
Horizon 3
AI Perpetual Innovation
Defensive Assets
Horizon 1
AI Foundations
Lighthouse Initiatives
1
2
3
4 5
Value
Time
Plan
Prove Scale
Improve
Align
Horizon 2
AI Community of Practice
Assets and Patterns
Wider Initiatives
2
3
4

37. Key Takeaways
01 | Enterprise AI in 2019, Trends & Challenges
02 | Practical steps to drive Enterprise-Wide AI Strategy
03 | Reference Framework for Execution and Scale
ALIGN IT PLAN IT PROVE IT SCALE IT IMPROVE IT

38. But there’s something no AI can
ever match,

39. And It’s Awesome Contino Stickers and Swag!
Stand R3
Come find us at our stand!
• Cool Swag
• Learn more about what we do
• Find your next career opportunity
Contact us
• Sydney and Melbourne Offices
• hello@contino.io
• www.contino.io