Artificial Intelligence & Generative AI
Speakers who decode the real-world impact of machine intelligence on industries, workforces and competitive advantage
Most large organisations have run AI pilots. Few have turned them into operating advantage. The harder problem is cultural: senior teams know they need to move faster on AI, but the internal mechanics of how decisions get made, how creative work is commissioned, and how risk is held have not caught up. Without that translation, AI sits adjacent to the business rather than inside it.
Most Western boards make capital allocation and supply chain decisions about China using mental models that are a decade out of date. The country has moved from manufacturing replica to setting the innovation standard in whole categories, even as its political and economic logic remains opaque. The result is a steady stream of strategic misjudgements at the moment when getting China right matters most.
Most leadership teams are not short of AI commentary. They are short of conviction about what to do with it. The harder question is which signals warrant a budget shift this year and which are noise dressed up as strategy.
Most boards overreact to economic news that will not matter in six months, and underreact to the news that will. A Fed decision or a fresh tariff round lands inside the business as margin compression and forecasts that stop working. Leaders need someone who can tell them which indicators will actually move the next two quarters of performance.
Most consumer technology ideas die in the gap between a working prototype and a business that can scale. The pressure comes from all sides at once: capital runs thin, distribution stalls, investors pass, and the founder has to decide what to keep building and what to cut. The organisations that want to back, buy, or learn from founders at that stage need an honest account of what the decisions actually look like from inside the company.
Most organisations understand that AI and digital transformation are not optional. The problem is the gap between acknowledging this and making irreversible decisions about infrastructure, talent, and operating models: particularly in industries built around physical assets and long capital cycles. Leaders in real estate, construction, financial services, and retail are being asked to future-proof portfolios before the technology landscape has stabilised. The consequence of moving too slowly and too fast look equally costly from a boardroom.
Assembling the right panellists solves one problem. Ensuring the moderator can hold their own in the conversation – in two languages, across AI, data governance, and autonomous systems – is another. Most technology organisations choose format over content knowledge, and the audience notices.
Most organisations have AI governance policies. Very few have a principled account of what those policies are actually trying to govern. The result is compliance frameworks that cannot answer the questions boards now face: when AI acts, who is responsible, and why.
Global supply networks were built for a world of open trade, cheap logistics, and predictable demand. None of those conditions hold any longer. Boards now face a live question: how do you keep cost discipline, meet customer commitments, and re-engineer operations for a fragmented tariff environment, all at the same time, and without stalling growth?
Most organizations are running AI somewhere. Getting it to run everywhere, consistently, strategically, at scale, is where senior leadership investment consistently stalls. The gap between a working pilot and an embedded enterprise capability is not a technology gap. It is a strategic and structural one: the wrong organizational design, insufficient data foundations, and a leadership layer that cannot distinguish between AI as a point tool and AI as a new operating logic.
Executive teams now have to talk publicly about AI in front of regulators, customers and their own workforces, and the conversations are getting harder. The technology is moving faster than the governance around it, and the room is full of people who have heard too many vendor pitches. What is needed is someone who can ask the questions a sceptical audience would ask, draw a straight answer out of a technical guest, and make the stakes legible to non-specialists in the room.
Leadership events convene senior executives at significant cost. The conversations they produce rarely justify it. When a moderator lacks genuine knowledge of the subject – AI adoption, fintech disruption, geopolitical risk – executives default to rehearsed positions. The insight the event was supposed to surface never arrives.