Scenario Planning & Strategic Foresight
Speakers who help organisations anticipate uncertainty, stress-test assumptions and plan for multiple futures
Boards are being asked to make consequential decisions about AI systems they do not fully understand, on timelines set by competitors, regulators and the technology itself. The vocabulary used inside these conversations, alignment, capability, existential risk, governance under uncertainty, was largely built by a small group of thinkers before the commercial AI race began. Without that vocabulary, leaders end up either dismissing the risk or capitulating to it.
Boards are being asked to make defensible decisions about exposure they cannot fully see: criminal networks embedded in supply chains, cyber intrusion routed through state actors, sanctions risk that shifts faster than legal opinion. The old separation between security, geopolitics and commercial strategy no longer holds. Leaders need a coherent picture of how these systems actually interact, written by someone who has spent decades inside them.
Most AI investment is still trapped in pilots, demos and isolated tools. The harder problem is redesigning how the organisation actually decides, staffs and operates once machines do meaningful work. Senior teams need a way to move from AI as a project portfolio to AI as the operating model.
Boards are being asked to make capital commitments against technologies that will not mature for a decade or more. Quantum computing, AI, biotech and energy are converging on timelines most strategy processes are not built to hold. Leaders need a credible read on what is physically possible, what is hype, and where the next decade of value will actually sit.
Strategy demands commitment, and commitment is what kills companies when the future does not arrive as forecast. Boards reward bold bets; the same bets concentrate risk in ways the planning cycle hides. The hard question is not which strategy to pick, but how to commit to one direction while keeping the option to be wrong.
Industry boundaries are moving faster than strategy teams can redraw them. Software firms, platforms and AI entrants now compete inside sectors that once felt structurally protected, and the rules of value capture have changed with them. Boards keep asking the same question: where in this ecosystem do we still own the customer, and where are we becoming a component in someone else’s stack.
Boards are making bets on Europe, India, and the transatlantic relationship without anyone in the room who has actually negotiated at that table. Macro briefings explain the weather. They do not tell you how Berlin will react to a tariff letter, what New Delhi will accept on market access, or how Washington reads a European industrial policy move. The gap between geopolitical headline and commercial decision is where serious money is being lost.
Boards keep hearing that frontier AI is either an existential threat or an inevitable productivity engine, and neither framing helps them set policy. Inside the firm, the practical question is sharper: which capabilities are safe to deploy, what governance is credible to regulators, and how do you tell hype from a real shift in the technology. Most leadership teams have no independent technical voice they trust to answer that.
European political risk is rarely as simple as reading election results. Governments form and fall through coalition mechanics that most business advisers, and most executives, cannot reliably read from the outside. For organisations operating across EU markets, the question is how to build genuine political intelligence into strategic planning before regulatory or institutional disruption arrives.
Most large companies still organise around the playbook that built them. The world they compete in now rewards faster cycles, ecosystem partners, and growth engines that sit outside the core. The hard question is no longer whether to transform, but how to run the existing business at full performance while building the next one alongside it.
Most organisations now run two AI agendas in parallel and neither one is working. The compliance agenda is ahead of the strategy agenda, and the strategy agenda is ahead of the operating model. Boards need a coherent way to think about AI as economic infrastructure, not as a procurement question, while the technology is still moving faster than their policies, their hiring, and their planning cycles can absorb.
Most organisations treat new ideas as intellectual problems – to be argued over, refined, and approved before anyone acts on them. That process is not a filter for bad ideas; it is a filter for action. The companies that build new things do not have better ideas. They have better discipline around testing the ones they have.