Product Managers need to enhance their skills in order to develop and provide AI related functional requirements specifications to engineering and data science teams. As a matter of fact, conversing with engineering and data science teams on AI and ML related topics are becoming extremely important communication skill for any product manager. If this is something you are facing today, don’t hesitate to join the workshop KEY TAKEAWAYS A hands-on workshop to learn new AI product development. You will get hands-on experience of defining & designing a product with AI & learn AI Product Thinking Principles. Learn about need for AI Product Thinking Approach Learn and practice key AI Product Thinking Principles Learn about UX Design and Product Management Principles for AI Product Develop/enhance your Product Idea (Existing or New) by practicing AI Product Thinking

1. AI Product ThinkingBuilding AI Product
using
AI Product Thinking

2. About Me: AI Product Management
Saurabh Kaushik
@saurabhkaushik
• Director, Product Engineering Management @Eureka.AI
• Help Telco's to monetize their data using AI and Data Products
• Engineered and deployed about 20+ AI Product Solutions
• Experience: 20+ years in various roles (Consultant/Lead/Architect/Manager/Director)
• Domain: FinTech, AdTech, MarTech
• Industry: Telco, Banking, Financial, Retail, CPG
• Tech: Data Science, ML, DL, NLP, Big Data, Java, Python, Full Stack
• Org: Products, Enterprise, Service, Tech Startups
• Speakers: Product School, NASCOM, World Startup Expo, Institute of Product
Leadership, IIMB, TechGigs, Product Leadership Forum.
• Hobbies: Tennis, Piano, Building Bots (Botreload.com)

3. Agenda
Why do we need AI
Product Thinking?
How to Apply AI
Product Thinking?
Workshop

4. Why do we need AI Product
Thinking?

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. Challenge #1: Dealing with Real World Data
Input
Output
Input
Output
Trained
Model
Explainable
Unbiased
Trustworthy
Unexplainable
Biased
Untrustworthy
Real World
Training
Traditional Products AI Products
Software
Programs
Logic
Processor
Algo
Processor

7. Challenge #2: Changing UX Dimension
UX
Product
Technology
UX
Product + AI
Technology
UX
AI Product
Technology
Pre AI Era AI-Inside Era AI-First Era
User User User
UX Design
Product Hierarchy
Pyramid
Alexa, Book
a Cab
Let me book a
cab on Mobile
Need to book
on Taxi Web
Portal
UX becomes narrow,
but needs to sharper.

8. Challenge #3: Managing User Expectation
Hereafter, What will you do and what will I do?
User
Expectation
Role Conflicts

9. Challenge #4: Zooming out to Product
UX / UI
Functional
Tech / AI Model
UX / UI
Functional
Tech / AI Model
AI Model is
the Product
This is the
Product
Product
Thinking

10. AI Product – Problem and Root Cause
Real World
Training
UX Design User
Expectation
Product
ThinkingUnexplainable Biased Untrustworthy

11. How to Apply AI Product
Thinking?

12. What is AI Product?

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. How to apply AI Product Thinking?
AI Product Thinking is a holistic approach of designing and developing Trustworthy, Unbiased and
Explainable AI Products by
• Redesigning User Experience for
AI ScenariosUX Design
• Reapplying Product Management
with AI best Practices
Product
Management

15. Where do you want to Go?
Augmentation
AI-Inside Era AI-First EraPre-AI Era
Customer Support
AI First Product Paradigm
Automation
AI-First Product cant exist without
AI.

16. Redesigning User Experience for
AI Scenarios

17. User Experience for AI Products
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

18. User Experience for AI Products
Identify what users
will STOP doing
Be very clear about what
users will KEEP doing
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

19. User Experience for AI Products
Show Confidence of Customer Satisfaction on
Automated Query Response
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

20. User Experience for AI Products
Show reason of these movies recommendations
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

21. User Experience for AI Products
Predicting Estimated Arrival Time along
with Expected Speed of Vehicle
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

22. User Experience for AI Products
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases

23. Find and handle weird edge cases
Racist behavior Insensitive behavior Inaccurate behavior
Define User vs Machine Role
Differentiate AI content visually
Explain how machines think
Set the right expectations
Provide an opportunity to give feedback
Find and handle weird edge cases
What If Tool

24. Reapplying Product
Management with AI Practices

25. AI Product Management
AI
PM
Vision
Strategy
Design
Execution

26. Vision - Visualizing the Future of Product
State Product Vision for Customer
(without Tech/AI)
Draw clear Value propositions
and differentiation with AI
Reimagine Product from AI
First/AI-inside era
Develop AI Product Vision
Statement

27. Vision - Visualizing the Future of Product
Customer Assistant Product to help customer resolve
their queries with high degree of satisfaction and
quick resolution in seamless and effortless manner.
State Product Vision for
Customer (without Tech/AI)
Draw clear Value propositions
and differentiation with AI
Reimagine Product from AI
First/AI-inside era
Develop AI Product Vision
Statement

28. Vision - Visualizing the Future of Product
State Product Vision for Customer
(without Tech/AI)
Draw clear Value propositions
and differentiation with AI
Reimagine Product from AI
First/AI-inside era
Develop AI Product Vision
Statement
• Pain/Gain Points - Inconsistent and error prone, lower
availability, longer resolution time, Higher Customer Input
cost
• Features: Intelligent and Intuitive Conversational UX, self
learning and fully automated Customer Care system.
• Benefits: Reliable, Faster, Contextual and Intuitive Query
Resolution with Chat Interface

29. Vision - Visualizing the Future of Product
State Product Vision for Customer
(without Tech/AI)
Draw clear Value propositions
and differentiation with AI
Reimagine Product from AI
First/AI-inside era
Develop AI Product Vision
Statement
Customer Service Product to automate query resolution
by using AI tech by addressing repetitive issues,
Automated Response Generation, Automated Handover
to Agent, Argument Agents with suggested replies, and
automating end-to-end resolution with least human
intervention.

30. Vision - Visualizing the Future of Product
Customer Assistant Product to help customer resolve their
queries with high degree of satisfaction and quick resolution
in seamless and effortless manner using AI enabled
automation of query resolution.
State Product Vision for Customer
(without Tech/AI)
Draw clear Value propositions
and differentiation with AI
Reimagine Product from AI
First/AI-inside era
Develop AI Product Vision
Statement

31. Strategy - Thinking about What to Build
Observe Product/Tech/Market
Trends with AI Impact
Ideate and prioritize features
to maximize ROI
Develop AI Product Strategy
with KPI for Biz/Tech/AI
Develop Product Roadmap
Business Model Canvas

32. Strategy - Thinking about What to Build
Observe Product/Tech/Market
Trends with AI Impact
Ideate and prioritize features
to maximize ROI
Develop AI Product Strategy
with KPI for Biz/Tech/AI
Develop Product Roadmap
Gartner Tech Trends – Hyper Cycle

33. Strategy - Thinking about What to Build
Observe Product/Tech/Market
Trends with AI Impact
Ideate and prioritize
features to maximize ROI
Develop AI Product Strategy
with KPI for Biz/Tech/AI
Develop Product Roadmap

34. Strategy - Thinking about What to Build
Observe Product/Tech/Market
Trends with AI Impact
Roadmap - Ideate and prioritize
features to maximize ROI
Develop AI Product Strategy
with KPI for Biz/Tech/AI
Develop Product Roadmap
Weigh False Predictions Precision Recall Trade Off

35. Strategy - Thinking about What to Build
Observe Product/Tech/Market
Trends with AI Impact
Ideate and prioritize features
to maximize ROI
Develop AI Product Strategy
with KPI for Biz/Tech/AI
Develop Product Roadmap

36. Design - Decide How to Build
Obsess with Customer and Data
in all decision making
Data Need - Train for Real
World Data
Adapt Breath-First approach
to build a product (MVP)
Feedback - Propagate/utilize
Flywheel effect of AI Products

37. Design - Decide How to Build
Obsess with Customer Needs and
their Data in all decision making
Data Need - Train for Real
World Data
Adapt Breath-First approach to
build a product (MVP)
Feedback - Propagate/utilize
Flywheel effect of AI Products

38. Design - Train for Real World Data
Design to handle noise in data
for consistent behavior
Design to handle biases in data
to avoid embarrassing scenarios
Design to handle acceptable
accuracy in production over
Product KPI
Design to handle anomalies for
edge cases
Obsess with Customer and Data
in all decision making
Data Need - Train for Real
World Data
Adapt Breath-First approach
to build a product (MVP)
Feedback - Propagate/utilize
Flywheel effect of AI Products

39. Design - Decide How to Build
Obsess with Customer and Data
in all decision making
Data Need - Train for Real
World Data
Adapt Breath-First approach
to build a product (MVP)
Feedback - Propagate/utilize
Flywheel effect of AI Products

40. Design - Decide How to Build
Obsess with Customer and Data
in all decision making
Data Need - Train for Real
World Data
Adapt Breath-First approach
to build a product (MVP)
Feedback - Propagate/utilize
Flywheel effect of AI Products

41. Execution - The Building Process
Follow Agile Development
(Define/Validate/Iterate)
Ensure Product fails gracefully
for edge conditions
Energize Cross Functional
Team Interactions
Monitor Product Behavior and
Customer Feedback

42. Execution - The Building Process
Follow Agile Development
(Define/Validate/Iterate)
Ensure Product fails gracefully
for edge conditions
Energize Cross Functional
Team Interactions
Monitor Product Behavior and
Customer Feedback

43. Execution - The Building Process
Follow Agile Development
(Define/Validate/Iterate)
Ensure Product fails
gracefully for edge conditions
Energize Cross Functional
Team Interactions
Monitor Product Behavior and
Customer Feedback

44. Execution - The Building Process
Follow Agile Development
(Define/Validate/Iterate)
Ensure Product fails gracefully
for edge conditions
Energize Cross Functional
Team Interactions
Monitor Product Behavior and
Customer Feedback

45. Execution - The Building Process
Follow Agile Development
(Define/Validate/Iterate)
Ensure Product fails gracefully
for edge conditions
Energize Cross Functional
Team Interactions
Monitor Product Behavior and
Customer Feedback

46. Workshop – Building a AI
Product using AI Product
Thinking

47. Interesting Quotes
“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 just AI Model" - Me ;-)

48. Thank you
AUTHOR: SAURABH KAUSHIK
TWITTER: @SAURABHKAUSHIK
LINKEDIN: @SAURABHKAUSHIK