Scenario Planning & Strategic Foresight speakers
Speakers who help organisations anticipate uncertainty, stress-test assumptions and plan for multiple futures
Speakers Associates represents 257 speakers on Scenario Planning & Strategic Foresight, including Michael Beckley, Kemal Apaydin, Peter Fisk, Mark Stevenson, Olivier Sibony, Thimon de Jong, Lucy Bullivant, Rita McGrath, Katja Schipperheijn and Graeme Codrington.
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.
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.
New leaders fail in their first ninety days more often than at any other point in their career, and the cost is paid by the team, the strategy, and the board that hired them. The same pattern repeats further up: senior teams face decisions where pattern recognition and systems thinking matter more than functional expertise, and most have never been taught either. Organisations need a repeatable way to accelerate leaders into new roles and to sharpen how their top team thinks.
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.
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.
Most boards now have an AI position on paper. Very few have a confident view of what their organisation should actually do with the technology, on what timeline, and at what cost to existing structures. The gap between AI as a slide in the strategy deck and AI as a real operating capability is where senior teams quietly stall.
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 strategic planning assumes a single, most-likely future. Organisations that fail mid-execution are often those with the best plans – built on one scenario rather than a map of probable outcomes. When conditions shift, teams that have modelled uncertainty act; those that have not, freeze.
Boards with exposure to the Middle East are being asked to make capital and operating decisions on a region where the analytical inputs are unreliable. Sanctions regimes shift, alliances re-form, and the gap between media narrative and on-the-ground reality has widened. Most external advisers can describe the policy. Very few can read the room.
Boards are being asked to make irreversible bets on AI, quantum, and biotech without a credible internal voice on where these technologies are actually heading. The instinct is to delegate the question to consultants who repeat last year’s consensus. That leaves the most consequential decisions with leaders who lack the horizon to judge them.
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.
Senior teams keep being surprised by events they could have seen coming. The traits that built their careers, conformity, consensus, command of detail, are the same traits that make boards slow to confront the unthinkable. The capability gap is not analytical, it is human: the willingness to name what is uncomfortable while there is still time to act.