1. CTIO, VP and Head of Data Technologies & Product 890 @ Capgemini INDIA
2. 26yrs exp Building Large Product, Engineering & AI/Analytics Driven Innovation
3. 13yrs @ Microsoft, 2.5yrs @ Jio, …
4. First AI Implementation @ Microsoft in 1999 for Outlook Product
5. Visiting Faculty & Speaker @ IIT, IIM, BITS Pilani, NITs, Conferences, Colleges
6. Board of Advisor to B-School, Engg Colleges, Institutes & Startups – Enable AI
7. Professional Coach & Guide
• Web Performance Improvements
• Delivering Successful Projects
• Applied Analytics & AI (in process)
Co-operation between man and
machine, as human intelligence
works in harmony with
Driverless cars, smart
robotics, the internet of
things, 3D printing
Internet and IT increase
automation and mass
Internal combustion engines,
airplane, telephones, card,
radio and mass production
Steam and water power
replace human and animal
power with machines
Future of AI and Analytics | Mukesh Jain | 7-Aug-2020
Speed and Agility
Users have choice…
Anytime, Anywhere and on Any device
Need to understand usage & Innovate
Growing Need for AI in Innovation
Compete on Data, Analytics & AI
Highest Individual Paid Person’s Opinion
…because I use it that way
I am sure about it / User wants this
The customer will never do that
User don’t know what they want
Users always want things free
How are (some) Decisions made?
•Which position should Ad be shown for a search query?
Should the home loan/credit card transaction be approved?
Which Video to show next on an Video app?
What recommendation can be given on e-commerce site?
How can I plan supply chain/logistics with current demand?
When should I release this movie to maximize revenue?
Why are my users leaving the app / service?
Values of qualitative or
Structured and Unstructured
Every activity or in-activity
Data tells a lot about somebody,
Useless, unless we can put a ₹ or $
Data... to Decision... to Action...
BI & Dashboard
Analytics & Forecasting
Business Outcomes & Results
What, How, Why
Validation and Next Steps
4 Quadrants of Artificial Intelligence
Systems that think
Systems that think
Systems that act
Systems that act
Evolution of AI
• Logic Rules
• No Learning
• Stats Knowledge
• System Learns
• No Contextuality
• System Constructs
• Explanatory models
• System Learns and
reasons with new
Data to Analytics to AI Journey
Cognitive Computing is the use of computational methods to:
Draw inferences from existing data.
Draw conclusions using an internal knowledge base.
Learn from past decisions by updating the knowledge base.
Artificial Intelligence describes cognitive computing systems with
completely intuitive interfaces for human users.
Machine Learning describes a set of computational methods &
techniques at the core of AI & Cognitive.
in the past?
Why it happened?
What will happen in
What should I do about
it? Cognitive & AI.
What haven’t I
Crash Analytics & Predictions
• “Send Error Report” button
• Will user send error report? Journey?
• Crash Analytics – Weekly Top 10 report
• User Data
• Machine Config / Interop / Add-in
Alerts during check-ins
User Behavior Driven Innovation
Identify top 25 user tasks for your product
Collective understanding of product usage
Office Ribbon – top task available, 1-2 clicks
Easy Discovery with the Innovative Design
Higher Adoption & Productivity
Outlook Junk filter
• The problem of 15K+ Junk email per day
• First ever AI project in Microsoft in 1999
• Personalized, based on individual users signals
• User Specific solution – server and client side
Design of Search User Experience
Color of Search
Why Blue? Which shades of
KPI & Results Data Driven
Future of Data, Analytics & AI
Data Literacy, Discovery and Collaborative Intelligence
Data Quality Management, Standardization and Commoditization
Proactive, Predictive, Prescriptive & Augmented Analytics
Reduced time to Insights with Self Service / Analytics As A Service
Tighter & Intelligent integration between Human & Machines with AI
Security, Privacy, Trust, Ethical AI, Explainability,
Data Scientist / Chief Data Officer / Chief Analytics Officer Mainstream
1. Try! “Poochne me kyaa jaata hai…”
2. A person with a new Idea is crank until the idea succeeds
3. Action without Results = Noise
4. If someone can find Mistake in your work, why can’t you yourself find it?
5. Focus on Knowledge – marks and success will follow
6. Only your “subhchintak” will give you candid feedback
7. Plan, Estimate, Track and Improve say-what-you-do & do-what-you-say
8. There is Learnings in everything - collect data and analyze
9. Do what you enjoy, you will never need to work – have Fun & get paid
10. Give back TIME to Community – teach/write/guide/mentor/coach
My Personal Learnings
Story >>> Let’s take a look through those challenges that organizations typically face. It could be all these and more:
organizational complexity on how to manage AI initiatives
adhesion of business to the initiatives
difficulties of IT to move beyond trial (lack of expertise or experience)
technology difficulties & uncertainty
uncertainty/fear of managing human impacts, etc.
And part of beginning to address these challenges demands a change of how we approach our AI projects...