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AI Product Thinking for Product Managers

A short presentation about, how to better design an AI Products using Product Thinking Principals meshed with AI Best Practice and learning from dealing with its Pitfalls.
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AI Product Thinking for Product Managers

  1. 1. AI Product ThinkingAI Product Thinking For Product Managers
  2. 2. About me (Professional Impact) Improved user personalization to Find Realtor through AI Intervention Increased Audience engagement by measuring their viewership on Digital and traditional channels. Helped them migrate native applications on Windows Embedded OS (CE) Enabled AI in Touchless Account Payable Enabled AI in Touchless Invoice to Cash Enabled AI in Financial Controllership Improved processing time and accuracy by automating Financial Compliance process through AI Built Media Optimization solution for Mobile Devices Built Contract and Product Entity Extraction for Retail/Banking Clients Built Customer Acquisition (Campaign Management) Platform for Telco Helped them innovate Smart Retail Banking through AI Built robust and scalable Private Cloud Platform for their Fright Business Faster processing and management of Investment Managed Funds Improved agility in their Drug Prescription and Invoice Processing through Digital Interventions Improved collaboration amongst various BUs of Asset Management – Corporate Investment Banking Digital Transformation of Payment System - Digital Banking Build Remote Controlled Customer Care Product for Broadband Telcom Customer Automated Product Onboarding and Cataloging Solution through AI Intervention Improved collaboration and Compensation processing with Insurance Brokers. Faster processing of customer billing and invoicing for Customers Helped their customers to share media effortlessly and view them elegantly on Mobile Built Web Security Framework for Business Portal Built Personalization Product API and Helpdesk Agent App for Zendesk.
  3. 3. Agenda Not Artificial Intelligence (AI) Not Tech Talk Not Product Management Not Product Thinking Not Design Thinking •Major Challenges with AI Product •What is AI Product Thinking? •Deeper dive in AI Product Thinking pure AI Product Thinking
  4. 4. Major Challenges with AI Product
  5. 5. Why AI Products need different Product Thinking ? Uber Self driving disaster (Untrustworthy) Microsoft Tay became racist (Biased) IBM Watson Oncology gave bad recommendations (Unexplainable)
  6. 6. Challenge: Dealing with real world data Input Output Input Output Trained Model Explainable Unbiased Trustworthy Unexplainable Biased Untrustworthy Real World Data Traditional Products AI Products Software Programs Logic Processor Algo Processor
  7. 7. Engine-First Product Paradigm Engine-Inside Era Engine-First EraPre-Engine Era Engine-first products are products that just would not make sense without Engine.
  8. 8. Challenge: Dealing with new Role between AI and Human AI-first products are products that just would not make sense without AI AI-Inside Era AI-First EraPre-AI Era Customer Service
  9. 9. What is AI Product?
  10. 10. Challenge: Designing UX for AI World UX Product Technology UX Product + AI Technology UX AI Product Technology Pre AI Era AI-Inside Era AI-First Era User User User
  11. 11. Challenge: Bring back the focus on Product UX / UI Functional Tech / AI Model UX / UI Functional Tech / AI Model AI Model is the Product This is the Product
  12. 12. What is AI Product Thinking?
  13. 13. What is AI Product Thinking? “Think in products, not in AI models” Minus AI Engineering Vision – Why are we doing this? Strategy – How are we doing this? Goals – What do we want to achieve? People – For whom are we doing this? Problem – What pain-point do we solve? Solution – What are we doing? Users
  14. 14. How to do AI Product Thinking? AI Product Thinking is a holistic approach of designing and developing Trustworthy, Unbiased and Explainable AI Products by Redefining new roles between AI and Human Redesigning User Experience for AI and Edge Scenarios Redrawing Testing mechanism to deal with real data Reapplying Product Management with AI best Practices
  15. 15. Redefining new roles between AI and Human
  16. 16. Man vs Machine
  17. 17. User Role • Product: Identify and deliver substantial value with which users will be comfortable with letting a machine replace. • UX: Identify and transition the change in most smooth, subtle and intuitive fashion. Identify what users will STOP doing • Product : Identify and renegotiate the deal between what humans to do and what machines do. • UX: Identify and maintain core features/controls to keen them in power seat. Be very clear about what users will KEEP doing Tech: Ensure, AI First to truly deliver new value with adequate levels of quality, reliability and demonstrability.
  18. 18. Redesigning User Experience for AI and Edge Scenarios
  19. 19. Differentiate AI content visually
  20. 20. Explain how machines think
  21. 21. Set the right expectations Predicting Estimated Arrival Time along with Expected Speed of Vehicle
  22. 22. Provide an opportunity to give feedback
  23. 23. User testing for AI products
  24. 24. Redrawing Testing mechanism to deal with real data
  25. 25. Find and handle weird edge cases Racist behavior Insensitive behavior Inaccurate behavior
  26. 26. Provide engineers with the right training data Design to handle real-world situations in all layers of Product Design to handle noise in data for consistent behavior Design to handle biases in data to avoid embarrassing scenrios Design to handle anomalies for edge cases Design to handle acceptable accuracy in production over Product KPI
  27. 27. Reapplying Product Management with AI Practices
  28. 28. AI Product Management AI PM Vision Strategy Design Execution
  29. 29. Vision - Visualizing the Future of Product Product Vision for Customer (without Tech/AI) Reimagine your Product from AI First/AI-inside era Draw clear Value propositions and differentiation AI Product Vision and Mission Statement Product to help customer resolve their queries 24/7 with high degree of satisfaction and quick resolution in seamless and effortless manner using AI-First Strategy. Product to offer AI based Customer Assistant system to deliver Trustworthy, Sensitive, Unbiased and Contextual query resolution through Conversational AI interface with automated real time learning using power of Deep Learning tech to serve 10M+ queries per day. High accuracy, relevancy, availability and automated learning loop at scale. Will deliver on competitive Customer Facing KPI with a ChatBot who understand domain best To develop an AI based Customer Assistant system which will resolve customer queries with high accuracy, relevancy, availability and automated learning loop at scale to serve 10M queries per day for certain business domain – Retail Banking.
  30. 30. Strategy - Thinking about What to Build Observe Product Trends with AI Impact Follow latest and great innovation in AI Develop AI Product Strategy and Roadmap Build KPI matrices for overall Product and AI model
  31. 31. Design - Decide How to Build Customer and Data Obsession in all decision making Build Product with Simpler AI Algo first Adapt Breath-First approach to build a product Consider scalability and performance in Product Architecture
  32. 32. Execution - The Building Process Follow Agile Development (Define/Validate/Iterate) Ensure Product fails gracefully for edge conditions Team Interaction: Understand fundamentals Monitor Product Behavior and Customer Feedback
  33. 33. Interesting Quotes To make human Interplanetary species - Elon Musk “Fall in love with a problem, not a specific solution“ — Laura Javier “Clean Thinking to Design Simple Product“ — Steve Jobs "Focus on Product thinking, instead of feature or AI model" - Me ;-)