AI changes nothing.

I have spent my career in roles where the existing playbook was never quite enough: sometimes because none yet existed, sometimes because the one in hand had to be challenged outright or reinvented.

I started with an MSc in Electrical Engineering and Computer Sciences, with a dissertation in Artificial Intelligence and Computer Vision, and an early career in mission-critical, deep-tech system development. I then co-founded and led a venture-capital-backed AI startup in San Francisco and Belgium, focused on speech recognition, turning research-grade AI capability into production-grade reliability before any operating template existed.

At McKinsey & Company, in the Strategy & Corporate Finance practice, I led engagements in M&A and corporate finance, large-scale transformation programmes and operational excellence for multinational companies, family-owned conglomerates and public-sector organisations in Europe, MENA and Asia.

The seventeen years that followed took me to the Middle East and Africa, in C-suite roles at LG Electronics and Royal Philips, in markets where the global headquarters approach needs substantial regional adaptation. The work spanned regional strategy, business modelling and go-to-market reinvention, new business building, innovation management, leading the healthcare consulting practice, transforming the regional solutions business, and growing the B2G practice.

AI changes nothing. Except everything.

It sounds like a contradiction, and it is meant to. Both statements are true at the same time, and much of the confusion around AI comes from holding only one of them.

AI changes nothing, in the sense that the fundamentals still decide who succeeds. A company still has to solve a real problem for customers who value the solution. It still has to create more value than it captures, and capture more than it costs. Organisations still decide, buy and change through people, trust and time. AI suspends none of these rules, and a large share of today’s AI spending is lost by teams who assume it does.

AI changes everything, in the sense that it multiplies each of these fundamentals in depth, breadth and speed, and makes possible what could not be done before. When building a product costs a fraction of what it did, choosing which problem to solve matters more than ever. When agents take on part of the work, teams, operating models and even the notion of the customer start to change. When nations, companies and individuals rely on AI for their decisions, who controls the data, the models and the compute becomes a strategic question.

I see this paradox from two vantage points.

At the leading edge, with Nexan Ventures, I back pre-seed founders building products that could not exist without AI, in Sovereign, Agentic and Physical AI. The founders who stand out take the fundamentals as seriously as the technology: a real problem, a real customer and a viable business model. They then use AI to go further and faster than was possible before.

Across the wider market, with Mosanya Advisory, I work with boards and leadership teams whose organisations now need to transform in the age of AI, whatever their sector or starting point. For them, the paradox reads the other way round. The technology is new, yet the outcome is still decided by a clear strategy, disciplined execution and adoption by the people who make the change work. My role there is to connect the three, so that the ambition turns into measurable impact.