Strategic Foresight x AI: From Signals to Scenarios
Masterclass and guest lecture at Copenhagen Business School’s Executive Education
A futures-focused AI session designed for leaders who need to make choices under uncertainty, combining foresight foundations, AI megatrend dynamics, and scenario thinking to build anticipatory leadership.
Challenge
AI is moving faster than most organisations’ ability to interpret and govern it. Leaders are surrounded by strong claims, dramatic timelines, and “inevitable” narratives, while their real challenge is more practical: deciding what to automate, where to insist on human judgement, how to avoid shallow adoption, and how to stay strategically responsible as AI capabilities and risks diverge.
This masterclass was built to help executives avoid two common traps at once:
Treating AI as a purely technical rollout, detached from values, incentives, and organisational design
Treating “AI futures” as prediction, rather than something to explore through scenarios and strategic choices
Approach
Key elements included:
Foresight 101 (decision quality, not prediction)
We grounded foresight as a systematic, participatory approach that tests choices against multiple futures, and highlighted how imagination deficits, herd mentality, and tunnel vision can distort AI strategy.Artificial Revolution as a megatrend (AI as system shift)
We framed AI as more than tools: a socio-technical transformation shaped by data, incentives, governance, and cultural assumptions, including distinctions between narrow AI (real) and strong/AGI (still speculative).AI-driven foresight in practice (augmentation instead of outsourcing)
We explored where AI can accelerate foresight (scanning at speed, synthesis, scenario support) and where it introduces risk (automation bias, blind spots, “cognitive debt,” generic outputs).Scenarios for AI futures (expanding the strategic imagination)
Participants worked with a structured set of five “AI transition” scenarios, from Plateau and Big AI to Diplomacy, Arm’s Race, and Take-off (based on IFCG’s work), using them as thinking tools to discuss plausibility, impact, and organisational implications.Anticipatory leadership (what we choose to preserve, automate, invent)
The closing synthesis focused on intentionality: humans give AI-driven change meaning through judgement, ethics, and choices about governance, skills, and long-term direction.
Outcomes
1) Leaders left with clearer “decision hooks” for AI strategy
Rather than debating AI in general terms, the masterclass sharpened the questions leaders need to answer: what must remain human, where AI can genuinely improve outcomes, and what governance is required to avoid accidental drift.
2) Scenario thinking replaced timeline fixation
By working with multiple AI futures, participants could stress-test assumptions and explore strategic implications without anchoring on a single predicted trajectory or hype-driven year-by-year forecasts.
3) A practical lens on the hidden costs of AI adoption
The session made risks tangible — from automation bias to cognitive debt — and equipped participants to treat “speed” and “scale” as design choices that must be balanced with responsibility and organisational learning.
