As a Senior AI Business Leader with over 20 years of experience at the intersection of technology and enterprise strategy, I've dedicated my career to a single mission: 𝘁𝗼 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝗮 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗔𝗜 𝗳𝘂𝘁𝘂𝗿𝗲.

I believe the greatest challenge for modern leaders is not just implementing AI, but doing so responsibly, sustainably, and in a way that creates tangible business value. I thrive on demystifying the complexities of technologies like Generative and Agentic AI and building the strategic frameworks that empower organizations to lead with confidence.

Having led large-scale digital transformations for global enterprises and mentored winning startups in the Stanford ecosystem, I bring a unique, "in-the-trenches" perspective to my work.

My professional life is built on two core pillars:
𝟭. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽:
In my role at G42, I lead the end-to-end delivery of complex AI products and platforms, build and mentor high-performing AI/ML teams, and partner with executive leadership to embed AI capabilities across all business functions.
𝟮. 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 & 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 (𝗔𝗜𝗘𝘅𝗽𝗼𝗻𝗲𝗻𝘁):
Beyond my corporate role, I am passionate about giving back to the global AI ecosystem.I partner with leaders and founders in four key ways:
➔ 𝗕𝗼𝗮𝗿𝗱 & 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗔𝗱𝘃𝗶𝘀𝗼𝗿𝘆: Providing independent, expert counsel to boards and C-suite leaders on AI strategy, governance, and risk oversight.
➔ 𝗔𝗜 𝗦𝘁𝗮𝗿𝘁𝘂𝗽 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽: Guiding ambitious founders from idea to impact through my 1-on-1 mentorship program and affiliations with Stanford's LISA and SEED Spark programs.
➔ 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗖𝗼𝗮𝗰𝗵𝗶𝗻𝗴: A confidential partnership for senior leaders looking to sharpen their strategic acumen and drive transformational change.
➔ 𝗦𝗽𝗲𝗮𝗸𝗶𝗻𝗴: Delivering engaging keynotes and workshops that translate complex AI concepts into actionable business insights.

𝗠𝗬 𝗘𝗫𝗣𝗘𝗥𝗧𝗜𝗦𝗘 𝗜𝗡𝗖𝗟𝗨𝗗𝗘𝗦:
▸ Generative & Agentic AI
▸ Responsible & Sustainable AI
▸ AI Strategy & Governance
▸ Digital Transformation
▸ Executive Leadership & Coaching

𝗠𝗬 𝗔𝗙𝗙𝗜𝗟𝗜𝗔𝗧𝗜𝗢𝗡𝗦:
I am honored to contribute to the global technology ecosystem as a:
➔ HBS Advisory Council Member
➔ MIT Technology Review Committee Member
➔ Stanford University Coach (LISA & SEED Spark)
➔ Forbes Technology Council Member
➔ IEEE Senior Member
➔ OneLeague Global Mentor

Let's connect. I'm always open to discussing how we can build the future of AI, together.

Ajay Pundhir

Excited to join the "Pilot to Policy: AI Safety" roundtable at Machines Can Think  2026, hosted by Women in AI in collaboration with MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)

The question we're tackling: What happens when AI moves from controlled pilots to messy reality?

In my experience, that's exactly where governance frameworks get tested—and where the gap between "responsible AI" as a slide deck and responsible AI as operational practice becomes painfully clear.

Looking forward to learning from this incredible group of practitioners who are navigating these challenges daily. 

Yasmin Al Enazi, Dr. Alessandra Sala, Nebahat Arslan, Emine Yilmaz Bütün, CPA, Henrik von Scheel, Alexis Jean-Baptiste, Sofia GHACHAM, Abdalla Swikir, Dr. Abir Haddad, Naiyarah Hussain نيَّاره حسين, Eng. Rwdah Al-Subaiey, Latifa AlShehhi, Dr. Abrar Abdulnabi Andrew Jackson, PhD Eric Xing Yann LeCun

Let's build future together!

#MachinesCanThink #AISafety #ResponsibleAI #MBZUAI

Ajay Pundhir أجاي بوندهير

A question came up in our strategy meeting last quarter that I've been wrestling with since.

"We've rolled out AI coding tools. The velocity numbers look strong. When does this translate to efficiency gains we can actually bank?"

Fair question. I didn't have a satisfying answer.

So I pulled the research. The picture is more complicated than the vendor decks suggest.

The controlled studies show genuine gains. MIT found 55% faster task completion, McKinsey reported up to 2x improvements. These findings are credible and worth taking seriously.

But METR's July 2025 study introduced an important caveat. When they measured experienced developers working in their own codebases, not greenfield exercises, AI users took 19% longer to complete tasks. More striking: they believed AI had helped them. The gap between perception and measured reality was 43 percentage points.

This isn't an argument against AI adoption. It's an argument for precision about where these tools add value and where they might be creating obligations we haven't fully accounted for.

CISQ estimates technical debt costs U.S. organizations $2.41 trillion annually. The MIT Sloan team argues AI-generated code carries a "higher interest rate" on that debt because it's harder to detect and fix.

I've written a longer analysis on what I'm calling the Governance Dividend, the competitive advantage that accrues to organizations treating AI governance as strategic infrastructure rather than compliance overhead. The research suggests a 20% pricing premium for trusted AI products, faster regulatory access, and critically, the ability to scale beyond pilots.

The organizations capturing lasting value won't necessarily be moving fastest. They'll be the ones who figured out what to measure.

Full Article: https://lnkd.in/dXvYk6Pd 

#AIStrategy #TechLeadership #AIGovernance #SoftwareEngineering AiExponent Andreas Welsch Stanford University Digital Data Design Institute at Harvard (D^3) HBS Club of the GCC Stanford LEAD Forbes

AI Productivity Paradox

Just published a framework I've been refining for years.

If you're evaluating AI initiatives — whether as a founder, exec, or board member — this might save you from the most common failure modes.

Every AI pilot starts with excitement.

Most end with "what exactly did we build?"

The problem isn't the technology. It's skipping the hard questions upfront.

I developed the AI Business Canvas — a one-page framework that forces clarity before you commit resources.

It covers 12 critical areas across 4 pillars:

STRATEGIC FOUNDATION
→ Core problem (the real one, not the assumed one)
→ Target persona and their current workflow
→ Value proposition that's 10x better

SOLUTION & FEASIBILITY
→ What the user actually experiences
→ Data strategy and cold start plan
→ Technical risks you're not talking about

IMPACT & VIABILITY
→ KPIs that tie back to business value
→ Business model and pricing
→ Go-to-market that actually works

RISK & RESPONSIBILITY
→ Competitive moat (not just features)
→ Responsible AI considerations
→ Non-technical risks that kill initiatives

I've attached the canvas as a PDF. Print it. Use it in your next strategy session.

For the full breakdown of each block, read the complete guide:
https://lnkd.in/eUxm2CNm

#AIStrategy #GenerativeAI #Leadership #Framework

AI Business Canvas

Companies that succeed with AI rarely score 5/5 on every pillar. What they do have is honest awareness of their gaps — and a plan to address them.

The danger isn't low scores. It's overconfidence.

Try this with your leadership team this week. Compare notes. The gaps you disagree on are where the real conversations need to happen.

#AI #Framework #Strategy #GCC Stanford University Graduate School of Business HBS Club of the GCC Stanford LEAD

73% of companies are integrating AI.

Most aren't ready.

"Ready" doesn't mean having the latest tools. It means alignment across 5 areas that most organizations ignore until it's too late:

𝟭. 𝗦𝗧𝗥𝗔𝗧𝗘𝗚𝗬
Do you have use cases tied to real business value?
Or are you doing "AI for the sake of AI"?

𝟮. 𝗗𝗔𝗧𝗔
Is your data clean, accessible, and governed?
Poor data quality costs companies 20% of revenue.

𝟯. 𝗧𝗔𝗟𝗘𝗡𝗧
Do you have the skills — or a plan to build them?
Does your culture tolerate experimentation?

𝟰. 𝗢𝗣𝗘𝗥𝗔𝗧𝗜𝗢𝗡𝗦
Can you deploy and monitor models in production?
AI isn't "set it and forget it."

𝟱. 𝗘𝗧𝗛𝗜𝗖𝗦
Who's accountable when something goes wrong?
Can you explain how your models make decisions?

I built this framework after watching organizations stumble on the same gaps repeatedly.

Score yourself 1-5 on each pillar. Where you're weakest is where to focus first.

Full breakdown with diagnostic questions:
https://lnkd.in/eVZQB-q4 

#AIReadiness #AIStrategy #DigitalTransformation

Curious where most teams score lowest?

From what I've seen:
• Startups: Guardrails (move fast, fix later)
• Enterprise: Observability (too many layers to trace)
• Research teams: Resilience (happy path is all they test)

What's your weakest area?

#AI #GenAI #RAG #Strategy Stanford LEAD HBS Club of the GCC

Is your RAG production-ready?

Most teams build a demo that "works in Jupyter" and assume they're close to deployment.

They're not.

I've seen this pattern repeatedly: impressive prototype in week one, months of debugging to get it production-stable.

Here are the 5 areas that separate demo RAG from production RAG. Score yourself 1-5 on each:

𝟭. 𝗘𝗩𝗔𝗟𝗨𝗔𝗧𝗜𝗢𝗡
Do you measure relevance and faithfulness automatically?
Not "it looks right" — actual metrics you can track.

𝟮. 𝗚𝗨𝗔𝗥𝗗𝗥𝗔𝗜𝗟𝗦
Do you filter harmful outputs before they reach users?
Hallucinations will happen. The question is whether you catch them.

𝟯. 𝗢𝗕𝗦𝗘𝗥𝗩𝗔𝗕𝗜𝗟𝗜𝗧𝗬
Can you trace failures back to specific retrievals?
When something breaks at 2am, can you debug it?

𝟰. 𝗥𝗢𝗨𝗧𝗜𝗡𝗚
Do you pull from multiple knowledge sources smartly?
Single vector store isn't enough for real workloads.

𝟱. 𝗥𝗘𝗦𝗜𝗟𝗜𝗘𝗡𝗖𝗘
Does your system degrade gracefully on edge cases?
Production traffic will surprise you.

Add up your score:
→ 20-25: Ship it
→ 15-19: Fix the gaps first
→ Below 15: Back to the lab

Scored below 20? I've open-sourced a production RAG engine with all of this built in:
https://lnkd.in/eWMNixbF

#RAG #GenerativeAI #AIEngineering #OpenSource

e& enterprise

As the leader of e& enterprise's Data & AI Practice across Asia, Middle East, Africa & Europe, I drive digital transformation and spearhead our AI initiatives to accelerate business growth and innovation. My multifaceted role encompasses:
•	Leading the Data & AI P&L unit, ensuring both technological excellence and financial performance
•	Developing and executing comprehensive Data & AI strategies tailored to regional markets
•	Managing sales, pre-sales, and business development efforts to expand our market presence and drive revenue growth
•	Overseeing the delivery of cutting-edge AI solutions, from ready-to-deploy accelerators to bespoke implementations
•	Guiding organizations through their AI journey, from maturity assessment to full-scale adoption
•	Fostering partnerships with key stakeholders to expand our AI ecosystem
•	Identifying M&A targets and investment opportunities in the AI space to expand our capabilities and market presence
•	Leading the AI Center of Excellence across e& operations, fostering innovation and best practices
•	Driving advancements in critical areas such as AI for sustainability and cybersecurity

With a portfolio of 200+ successfully implemented use cases across various sectors including Banking & Insurance, Public Sector, Retail, Oil & Energy, Healthcare, Education, Logistics, Real Estate and Telecom, my team is at the forefront of AI-driven business transformation.

I am passionate about unlocking the potential of data and AI to solve complex business challenges and create lasting value. My focus is on bridging the gap between advanced technology and practical business applications, ensuring our clients stay ahead in the rapidly evolving digital landscape while driving growth for e& enterprise.

Specialties: AI Strategy, Data Analytics, Machine Learning, GenAI, Digital Transformation, Business Development, Innovation Management, Cross-Cultural Leadership, Strategic Partnerships, M&A in AI, P&L Management

Head of Data & AI Practice | Asia, Middle East, Africa and Europe

• Heading the International Center of Excellence for Artificial Intelligence (AICoE) operating across Asia, Middle East and Africa, creating the International AI strategy and using AI/ML to solve real-life business problems across functions and verticals at e&
• Building, designing, deploying and maintaining cutting edge AI/ML models with a large team of data scientists, data engineers and domain experts to create business impact across the organisation 
• Leading the Group Customer Value Management (CVM) Strategy and Operations covering Product & Pricing, Advanced Analytics, building and managing real-time and contextual Communication Channels, Campaign management, creating data lakes and managing big data platforms, digital integration and building new system capabilities 
• Establishing global strategic partnerships and alliances with all partners in the AI ecosystem and beyond
• Consulting and providing AI-as-a-service/Data-as-a-service/CVM-as-a-service to Telcos and other enterprises globally across sectors and industries
• Business development for global client acquisition and Go-to-Market strategy.
• Identifying M&A targets and other investment opportunities in the AI space
• Generating insights, dashboards, business intelligence and Commercial reporting

Vice President, AI, Advanced Analytics and CVM | Asia, Middle East and Africa

Director, Consumer | Asia, ME, Africa | Group CVM, Loyalty & Analytics | Head CoE Advanced Analytics

Etisalat

Director, Consumer | Group CVM, Loyalty & Analytics | Center of Excellence for Advanced Analytics

Managing Customer Value Management (CVM) and Analytics for Etisalat operations across Asia, Middle East and Africa

Director, Customer Intelligence | Etisalat Group Customer Value Management (CVM) & Analytics

Deloitte

Associate Director, Consulting, Strategy & Operations, Technology, Media and Telecom

KPMG India

Strategy Consulting for Telecom, Media and Technology
Business development across Middle-East, Africa, South East Asia, Europe and India.

Led multiple engagements with a varied telecom and media clientele focusing on Customer Value Management, Customer Experience Management, Revenue maximization, Product/Pricing Strategy, EBITDA Enhancement, Process Optimization, Advanced Analytics & Modelling, Business Transformation, Sales and Distribution Strategy, Market Entry Strategy

Associate Director, Management Consulting, Strategy and Operations, Telecom, Media & Technology

Idea Cellular Ltd

Head of Product, Pricing and Customer Value Management & Analytics, General Manager, Marketing

Leading the Product Team with end to end responsibility of Product Planning, Product Strategy, Pricing (Commercials), Road-map, Go to Market Strategy & deployment, Analytics, Customer Life cycle Management (CLM), Sales, Marketing and communication for the Prepaid Business (Acquisition & U&R), Postpaid Business - Retail and Enterprise (Acquisition & U&R), Enterprise Business Solutions and Domestic/International Roaming Business.

Head of Product, Pricing, Customer Value  Management & Analytics - Deputy General Manager, Marketing

Deputy General Manager (DGM), Marketing
Responsible for planning, strategizing, coordinating and managing all activities of Postpaid – Retail & Enterprise Business (Acquisitions) at the National Level.

Country Head Postpaid Business - Retail and Enterprise Business, DGM, Marketing

Senior Manager, Marketing
National Head, Postpaid Business for Retail & Enterprise

National Head, Postpaid Business for Retail & Enterprise, Marketing

Senior Manager, Marketing, PCO & FWP Business
National Head, PCO & FWP Business (Prepaid Acquisitions & UnR)

National Head, PCO & Fixed Wireless Phone (FWP) Business, Marketing

Manager, Marketing

Manager, Sales & Marketing

Citi

Summer Training in the Consumer Business Area

Summer Trainee

MUFG

Worked in the Foreign Exchange and Deposits departments

Graduate Management Trainee

BNP Paribas

With over 20 years of Consulting and Industry experience in the field of Artificial Intelligence, Customer Value Management, Product Management, Business Development  and Strategy, Amit brings with him extensive knowledge and deep understanding of working in the domain of mobile technology and telecom. 

He is currently Vice President, AI, Advanced Analytics and CVM at e&, UAE. He leads the Group CVM, Loyalty and AI & Analytics function and also heads the International Center of Excellence (CoE) for Artificial Intelligence (AI).

He has earlier held the positions of Associate Director, Management Consulting at Deloitte & KPMG, Head of Product, Customer Value Management & Analytics, Country head for Postpaid, Public Call Office and Fixed Wireless Phone Business at Idea Cellular Ltd. (Aditya Birla Group) 

Working in this high-growth mobile industry all these years has given him valuable experience of dealing with mobile device manufacturers, operators, consultants, related start-ups, and provided opportunities to negotiate complex deals and understand nuanced product issues. 

With his skills for strategic and operational excellence, he has been able to successfully lead and transform key businesses into high performance units. 

In recognition of his well demonstrated leadership skills, entrepreneurial spirit and passion for pursuing excellence, he was awarded the Chairman’s Award (Aditya Birla Group) for outstanding business performance. At e& (Etisalat) he was awarded the North Star and Outstanding Project Contribution Awards for his outstanding work and contribution towards AI and advanced analytics.
He has also been conferred upon the 40 under 40 data scientist Award (2022) and the Top 100 most influential AI and Analytics Leaders (2022) by the prestigious Analytics India Magazine (AIM). 
 
He is a regular guest speaker across leading International B-schools (IIML, IIMK, IIMR, IIMS, IMT Dubai, SPJain Dubai, TAPMI, NMIMS, Symbiosis & others), Faculty Development Programs and International Conferences/Seminars

Amit is an Executive MBA from London Business School (LBS), MBA from Institute of Management Technology (IMT), Ghaziabad and a commerce graduate from Shri Ram College of Commerce (SRCC), University of Delhi. 

Specialties: Artificial Intelligence, Advanced Analytics, Customer Value Management, Business Strategy, Product Management, Business Development, Product/Pricing Strategy, Micro-segmentation, Business Analytics, Digital Transformation Building New Business & Models, Customer Experience, Sales & Distribution, Marketing and Communication

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