Ajay Pundhir
Founder, AI Exponent LLC (AskAjay.ai) | AI Strategist | SpeakerAskAjay.ai
Skills
About
Ajay Pundhir is the Founder of AI Exponent LLC, the company behind AskAjay.ai, and Group Director, Data Analytics and AI at the Investment and Development Office, Government of Ras Al Khaimah. He helps leaders make AI real. For fifteen-plus years he has built AI inside large organisations, first at Nokia, Samsung Research and American Express, then at Presight, a G42 unit in Abu Dhabi, where he joined the early founding team. What those years taught him is that enterprise AI rarely stalls because of the model. It stalls on governance, on incentives that pull the wrong way, and on nobody being clear about who decides. That lesson shapes the advisory practice at AskAjay.ai, where boards and senior executives bring their AI strategy, governance and agentic transformation questions. Founders building AI companies come to him for mentoring as well. Underneath the work are five frameworks of his own: MVG, PRIME, Trust Premium, Liability Ledger and A7. There is also the Situation Room, an AI governance intelligence system built on his published writing. Ajay holds IEEE Senior Membership and is a member of the HBR Advisory Council, the MIT Technology Review Expert Panel and the Forbes Technology Council. As a Startup Mentor he works with Stanford SEED Spark and Stanford LISA, and he is on the One League Global Mentorship Board. His fortnightly newsletter, The Brief, covers AI strategy and governance for senior leaders. He is based in Abu Dhabi.
Ajay Pundhir
Published content
expert panel
Anthropic’s initial public offering (IPO) highlights a turning point for the artificial intelligence industry. As demand for AI accelerates, the enormous costs of developing, delivering and scaling the technology are raising new questions about profitability, risk and long-term sustainability.The company's first-half 2026 financial disclosures illustrate the challenge: Anthropic reported $16.3 billion in revenue alongside a net loss of approximately $80.7 billion, much of it attributable to noncash accounting adjustments. The figures underscore why strong demand and rapid growth don't necessarily translate into sustainable economics.For business leaders, the implications extend well beyond one company's IPO. Members of the Senior Executive AI Think Tank, a curated group of experts specializing in machine learning, generative AI and enterprise AI applications, share their perspectives on what comes next. Drawing on their experience in technology, investment, enterprise transformation and business strategy, they explain why the next phase of AI will demand more than innovation: It will require financial discipline, responsible governance, adaptability and a clear path to lasting business value.
expert panel
As artificial intelligence transforms how organizations operate, the traditional sources of professional advantage are shifting. Younger, AI-native employees may have an edge in adopting emerging tools, experimenting with new technologies and accelerating execution, but experienced leaders bring institutional knowledge, strategic perspective and the judgment developed through years of navigating complex business decisions.However, the divide between these groups may be less important than what happens when they work together.According to the World Economic Forum's Future of Jobs Report 2025, 39% of workers' existing skill sets are expected to be transformed or become outdated by 2030. Although AI and big data are among the fastest-growing skills, analytical thinking, resilience, leadership and creative thinking remain essential capabilities.Members of the Senior Executive AI Think Tank, a curated group of experts specializing in machine learning, generative AI and enterprise AI applications, suggest that neither technological familiarity nor years of experience will be enough on its own. Below, they explore how AI is changing the value of experience, what skills will matter most and how companies can prepare their workforces for what's ahead.
expert panel
Sep 18, 2026
Startup fundraising has always followed a familiar formula: build the product, prove traction, raise enough money to reach the next milestone.But AI is disrupting that formula. Models change quickly, inference costs fluctuate, enterprise sales cycles can stretch for months and today’s breakthrough feature can become tomorrow’s commodity. The assumptions behind a traditional runway or growth plan can change before a company reaches its next round.That means AI founders need to rethink what they are raising capital to prove. Is it customer demand? Technical feasibility? Sustainable unit economics? Enterprise readiness? Or a durable advantage that can survive the next model release?Founders shouldn’t just consider how much money their startup can raise, but what that capital needs to accomplish—and what evidence it should produce along the way.Members of the Senior Executive AI Think Tank—a curated group of executives and practitioners working across machine learning, generative AI and enterprise AI applications—share the fundraising advice they believe AI founders should leave behind, from chasing maximum capital to relying too heavily on traditional traction, and what investors should see instead.
expert panel
Sep 11, 2026
AI agents are becoming capable of doing more than generating information—they can now analyze code, identify vulnerabilities, write potential exploits and interact with the systems they are designed to help secure. Those capabilities can dramatically accelerate security work, but they also introduce new risks when an agent can move from identifying a problem to taking action without human intervention.So where should companies draw the line between useful autonomy and unacceptable risk? And what should an AI agent be allowed to do independently when its actions could affect production systems, sensitive data or security controls?Members of the Senior Executive AI Think Tank—a curated group of experts specializing in machine learning, generative AI and enterprise AI applications—examine how leaders can use sandboxing, least-privilege access, deterministic controls and human oversight to contain risk, while also addressing less technical questions around liability, accountability and reversibility. Together, they offer a practical framework for deciding not just what AI agents can do, but what organizations should actually allow them to do.
expert panel
Artificial intelligence remains one of the most consequential forces reshaping business, yet many organizations still struggle to distinguish meaningful breakthroughs from attention-grabbing headlines. While public discussion often centers on increasingly powerful models, digital assistants and speculation about artificial general intelligence, many enterprise leaders are discovering that the most transformative AI developments occur behind the scenes.Ask 10 AI experts what will matter most a year from now, and you might expect 10 different answers. Instead, members of the Senior Executive AI Think Tank—a curated group of experts specializing in machine learning, generative AI and enterprise AI applications—arrived at a strikingly similar conclusion: The biggest opportunities—and risks—aren't tied to the next model release. Across industries, they point to the infrastructure that makes AI useful in practice, from governance and security to evaluation, trust and workflow integration. At the same time, many are skeptical of some of today's loudest predictions, particularly around fully autonomous agents replacing human judgment at scale.As recent research from McKinsey suggests, organizations are increasingly finding that AI success depends less on access to cutting-edge models and more on the ability to operationalize them effectively. The experts featured here—those on the front lines of AI innovation—share the developments they believe leaders are underestimating, the trends they think are overhyped and where executives should be investing now to create lasting competitive advantage.
expert panel
As multimodal AI moves rapidly from novelty to baseline expectation, companies are confronting a deeper challenge than simply adding new features. Users increasingly expect software to understand text, voice, images and video simultaneously, while preserving context seamlessly across every interaction. That shift is forcing organizations to rethink how products are designed, architected and differentiated.Members of the Senior Executive AI Think Tank say the next era of product competition will center less on standalone AI capabilities and more on orchestration, workflow intelligence and trust. Their insights arrive as major technology companies race to integrate multimodal capabilities into mainstream applications. Multimodal systems capable of understanding and generating across formats are becoming foundational to enterprise software strategy. At the same time, organizations are discovering that simply embedding AI into existing workflows does not automatically create better user experiences.Instead, experts argue, multimodal AI is changing the very definition of interface design. Products are evolving from static tools into adaptive systems that anticipate intent, reduce friction and collaborate more naturally with users. The insights that follow explore why multimodal AI is forcing companies to rethink everything from UX design and workflow orchestration to trust, memory and product differentiation—and what leaders must do now to stay competitive.
Company details
AskAjay.ai
Company bio
AskAjay.ai is the advisory and thought leadership practice of AI Exponent LLC. Ajay Pundhir founded it for the people who have to make AI work inside a real organisation: boards, senior executives and the founders of AI companies. There are four services. Agentic transformation. Strategic AI advisory. AI startup advisory. Speaking. Each one draws on five frameworks Ajay created, from MVG (Minimum Viable Governance) for standing up governance that works, to A7 for judging whether an organisation is ready for autonomous agents. PRIME, Trust Premium and Liability Ledger complete the set. Engagements regularly touch the EU AI Act, the NIST AI Risk Management Framework and ISO 42001. The practice also runs the Situation Room. It is an AI governance intelligence system that answers strategic questions, cites a source for every recommendation, and says plainly where AI guidance stops and a human has to decide. The belief behind all of it is simple. Organisations that govern AI well get more out of it.