Polynome Group’s Alexander Khanin on closing the AI leadership gap in the UAE
The founder of Polynome Group explains why leadership, not technology, is holding back AI at scale and how the AI Academy aims to change that
21 April, 2026
TT
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As governments and businesses race to turn AI ambition into real economic value, a gap is becoming harder to ignore; strategy is moving faster than execution. In the UAE, where national targets for AI-driven growth are among the most ambitious globally, the challenge is no longer access to technology, but whether leadership is equipped to deploy it at scale.
Alexander Khanin, founder of Polynome Group, is working at that intersection through the Polynome AI Academy, an initiative designed to prepare senior decision-makers for an AI-led future.
In this conversation, he breaks down why leadership, not technology, is now the bottleneck, and what it will take to bridge the gap between experimentation and real-world impact.

The AI Academy was launched last year by Polynome Group and unveiled during the Machines Can See Summit. Tell us about the AI Academy and why it was created?
Polynome AI Academy was launched by Polynome Group and unveiled during the Machines Can See Summit in the presence of Sheikh Nahyan bin Mubarak Al Nahyan, Minister of Tolerance and Coexistence.
We built this initiative because we saw a critical disconnect. The UAE has one of the most ambitious AI strategies in the world, targeting Dhs335bn in additional economic growth by 2031, but many business leaders responsible for executing that strategy are not fully prepared to leverage AI at scale. According to 2025 research by Boston Consulting Group (BCG), only 5 per cent of companies globally generate substantial value from AI at scale. The gap is not access to technology; it lies in leadership capability.
AI is expected to guide half of all business decisions by 2027. The AI Academy’s goal is to produce leaders who can make those decisions confidently. We aim to create a new generation of AI-literate executives who actively drive AI adoption, equipping them with strategic frameworks, governance models, and practical implementation knowledge to do so responsibly.
Every graduate from our first cohort has either launched new AI initiatives, accelerated existing ones, or is planning new frameworks for implementation within six months. This level of conversion demonstrates the real and pressing need for AI leadership development.
What programmes does the AI Academy currently offer, and which leadership roles and industries are you primarily targeting? When is the latest upcoming programme about?
Our flagship is the Executive Program for Chief AI Officer, developed in partnership with Abu Dhabi School of Management, a 10-day intensive in Abu Dhabi comprising 10 modules, executive seminars, case labs, site visits to UAE AI institutions, and policymaker roundtables.
The programme is designed for senior leaders, including chief AI officers, CTOs, CIOs, CISOs, and advisors, in both the public and private sectors. It targets leaders across energy, finance, healthcare, government, and logistics.
The faculty includes experts from leading organisations such as NVIDIA, BCG, Mubadala, G42, AI71, NYU Abu Dhabi, Khalifa University, and ETH Zürich.
The AI Academy plans to expand internationally with a May programme in Munich focused on robotics, industrial automation, and physical AI. Our vision is to become the go-to institution for AI leadership education.
What are some of the questions asked during training?
Many organisations are already testing multiple AI initiatives simultaneously. The challenge is deciding which ones actually deliver business value and deserve further investment, so the question we consistently hear is, “We have 40 AI pilots, how do we know which ones to scale?”
That tells you everything about where most organisations are stuck. Other recurring themes: How do I evaluate AI vendor claims without a technical background? What does responsible AI governance actually look like in practice, not in a policy document? How do I restructure my team when AI changes what half of them do?
These may sound like technical questions, but in reality, they expose a leadership issue. The bottleneck is strategic clarity, and that is exactly where we focus.
The UAE ranks among the top countries for AI readiness and investment. What are some of the changes we are seeing in the country in terms of AI that will support future economic growth?
The UAE is moving from strategy to infrastructure at a remarkable speed. The AI market here is projected to generate over $46bn by 2030. Several federal entities have already brought in chief AI officers to steer initiatives and make sure projects actually deliver impact.
Public-private partnerships are supporting this growth as well. The US-UAE AI Acceleration Partnership is creating the largest AI campus outside the US, while Microsoft’s $15.2bn investment and the development of sovereign cloud capabilities are providing the foundation for advanced AI projects. These efforts are helping the UAE build sovereign AI capability, keeping the value local and setting the stage for sustainable, long-term economic growth.
The UAE is expected to add over one million jobs by 2030, with demand for tech roles rising by 54 per cent. What skills are organisations missing right now, and how can leaders close this gap quickly? How is the Academy helping organisations address the AI skills gap and shape practical AI roadmaps for real-world deployment across industries?
Research shows that 47 per cent of C-suite leaders say their organisations deploy AI too slowly, with 46 per cent citing talent skill gaps as the top reason. The real gap is at the leadership level: executives who can evaluate AI use cases, restructure workflows, manage change, and govern AI responsibly. Boston Consulting Group (BCG) found that when leaders demonstrate strong support for AI, employee adoption confidence jumps from 15 per cent to 55 per cent. Leadership is the multiplier.
The academy addresses this directly. We don’t teach executives to code. We teach them to ask the right questions, build operating models, and make investment decisions they can defend.
From our first cohort: 93 per cent say their AI strategy and roadmap capabilities improved, 86 per cent have already changed their organisation’s AI governance or operating model, and 57 per cent apply programme frameworks weekly or monthly. Participants leave with an AI roadmap specific to their business, not a generic framework.
What to ask before deploying AI at scale: the executive checklist for readiness, from data foundations to change adoption and workforce capability?
Five questions every leader should answer before scaling AI.
First, data foundations: Is your data accessible, governed, and trustworthy, or trapped in silos? Second, problem-value fit: Are you solving a real business problem or chasing a trend? Only 20 per cent of organisations have redesigned workflows when deploying AI, the rest just layered it on top. Third, governance: Who is accountable when AI makes a consequential decision? If you can’t answer that in one sentence, you’re not ready. Fourth, change adoption: Have you invested in training? Employees with at least five hours of structured AI training are significantly more likely to become effective users. Fifth, workforce capability: Do you have the talent to operate AI systems after deployment and not just during the pilot? If any answer is unclear, that’s where to start.

























