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A Data Driven Roadmap to Enterprise AI Strategy (Sponsored by Contino) - AWS Summit Sydney

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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.

A Data Driven Roadmap to Enterprise AI Strategy (Sponsored by Contino) - AWS Summit Sydney

  1. 1. S U M M I T SYDNEY
  2. 2. A Data-Driven Roadmap to Enterprise AI Strategy Yun Zhi Lin, Head of Engineering at Contino
  3. 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. 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. 5. Enterprise AI in 2019, Trends and Challenges Source: still from Blade Runner 1982
  6. 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. 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. 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. 9 2019 - Enterprise AI Roadblocks
  10. 10. Trust my “gut feel”! 2019 - Enterprise AI Roadblocks Have more Strategy! Execute without Strategy! Analysis paralysis or duplicate initiatives
  11. 11. Misaligned pocket AI initiatives Need more Skills Unknown Unknowns! Experiment! I have Bad Data 2019 - Enterprise AI Roadblocks
  12. 12. Patterns? Automation? 2019 - Enterprise AI Roadblocks Business vs IT Compliance as an Afterthought? Ethics? Consumer Data Right?
  13. 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. 14. Practical steps to drive Enterprise-Wide AI Strategy
  15. 15. Remember these are our Challenges
  16. 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. 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. 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. 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. 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. 21. Vision Alignment Photo from Contino Exec Data Roundtable 2019 ALIGN IT
  22. 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. 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. 24. Planning & Assessment PLAN IT
  25. 25. Picking the Right Lighthouse MVP LargeLow Low Small Long High Short Business Sponsorship Duration Importance Project Size Pick this project Data Quality
  26. 26. Multi Disciplinary AI Squad Engineers Data Scientists UX Business SMEs Customers Site Reliability Engineer“Brent”
  27. 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. 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. 29. Reference Framework for Execution and Scale PROVE IT SCALE IT IMPROVE IT
  30. 30. Treat SageMaker like Cattle! Not Pet!
  31. 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. 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. 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. 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. 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. 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. 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. 38. But there’s something no AI can ever match,
  39. 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

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