Artificial Intelligence & Generative AI
Speakers who decode the real-world impact of machine intelligence on industries, workforces and competitive advantage
Most organisations have AI budgets. Most are still running pilots. The problem is not investment – it is that AI has been framed as a strategy in its own right, which turns a deployment decision into an open-ended design problem. Meanwhile, the gap between AI experimentation and scaled competitive advantage is narrowing fast. Organisations that cannot move AI into production – aligned to business goals they already have – will cede ground to those that already have.
Most retail and consumer businesses can list the trends shaping their category. Few can turn that awareness into operational change before competitors do. The gap is not insight, it is the discipline to test, adapt, and scale what works while leaving the theatre of innovation behind.
Most organisations still treat technology as something the user picks up, looks at and puts down. That model is breaking. Sensors, haptics and ambient computing are moving the interface into the body, the garment and the room, and the businesses building for that shift need product leaders who can think across hardware, software and human design at once.
Organisations are deploying AI in hiring, healthcare, and operations before they understand whose assumptions are encoded in those systems. AI bias is not a data problem – it is a design problem, and it traces directly to the homogeneity of the teams building the tools. The second risk is less visible: research shows that humans routinely defer to automated systems in ways that go well beyond the reliability of those systems, including in high-stakes scenarios. Boards that have approved AI adoption have often not reckoned with either problem.
Executive conversations on markets, policy and geopolitics rarely fail for lack of material. They fail when the person in the chair cannot press a CFO, a central banker and a trade minister with the same confidence, or hold a room when the news changes between rehearsal and showtime. The cost is a flagship event that reads as polite rather than sharp, and a leadership team whose message never lands.
Strategy cycles run on three-year horizons. The technologies reshaping markets operate on ten-year ones. Without a methodology for reading early-stage signals, organisations discover the future after competitors have already acted on it.
Most leadership teams cannot tell which emerging technologies will reshape their business and which are noise. They commission AI pilots, IoT proofs of concept and digital programmes without a coherent picture of how these pieces will sit together five years out. The gap is not capacity to experiment. It is the absence of a credible long-range view that operating decisions can be anchored to.
Every established organisation faces the same structural trap: the systems that make it excellent today are precisely what prevent it from building what it needs tomorrow. Budget cycles, governance structures, and talent incentives are designed to protect the core – not to fund the experiments that will eventually replace it. The problem is not a lack of innovation ambition; it is the absence of a working architecture that lets both agendas run simultaneously, with different logic, without one destroying the other.
Most enterprises have run AI pilots. Far fewer have moved AI into the operating fabric of how decisions are made, deals get done, and software gets bought. The gap is not technology. It is a leadership problem about which workflows to redesign, which vendors actually deliver, and how to read the buyer signals coming back through the data.
Most boards have approved a digital strategy and an AI roadmap. Few can say with confidence what their company would look like if either succeeded. The gap between announced ambition and operating substance is widening, and the leaders most exposed are the ones who treated digital and AI as IT projects rather than as questions about how the business itself runs.
Digital transformation has become the flag every board agenda flies. The hard question is which parts of the business model actually change, who is accountable for the outcome, and how governments and regulators will reshape the ground beneath a strategy as it is being executed. Leaders who treat technology, policy and strategy as separate conversations keep losing the argument in all three.