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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteAI literacy helps people understand and assess AI systems; strategic foresight helps organizations explore plausible futures and prepare for change. The two capabilities solve different problems, and they work best together. Calling foresight the AI age’s “missing capability” is a useful provocation—not a finding that research has proved universally true.
What is strategic foresight?
Strategic foresight is a disciplined way to explore multiple plausible futures and consider how to prepare for them. It is not a method for predicting one certain outcome. As the OECD puts it, “Strategic foresight is not about predicting a single future.”
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Instead, foresight helps decision-makers notice change, test assumptions, and consider opportunities and challenges that different futures could create. OECD identifies methods including:
- Horizon scanning: looking for early signals of change.
- Megatrends analysis: examining broad forces that may shape the future.
- Scenario planning: developing and exploring multiple plausible future situations.
- Visioning and back-casting: describing a desired future and reasoning backward to identify steps that could help reach it.
These methods do not remove uncertainty. Their value is in helping people think beyond a single expected outcome and consider how present choices might fare under different conditions.
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How is strategic foresight different from AI literacy?
AI literacy and strategic foresight are related, but they focus on different questions. The OECD and European Commission’s 2026 AI-literacy framework describes knowledge, skills, and attitudes that help learners understand AI systems, critically evaluate their outputs, and use AI ethically and creatively. Its stated scope is primary and secondary education, so it is a useful grounding for the term—not a complete framework for professional skills.
| Dimension | AI literacy | Strategic foresight |
|---|---|---|
| Primary question | How does this AI system work, and should I trust or use its output? | What plausible futures could unfold, and how should we prepare? |
| Time orientation | Understanding and evaluating AI in present use. | Emerging signals, longer horizons, and alternative futures. |
| Typical methods | Understanding systems, critically evaluating outputs, and considering ethical use. | Horizon scanning, megatrends analysis, scenario planning, and visioning or back-casting. |
| Decision output | Better-informed decisions about using AI. | Strategies and options designed with multiple plausible futures in mind. |
| A potential failure mode | Relying on an AI output without adequately assessing it. | Treating one scenario as a forecast, or failing to turn scenarios into decisions. This contrast follows from foresight’s purpose; it is not a measured comparison. |
Put simply, AI literacy helps people judge a tool and its output. Foresight helps them think about how circumstances may change and what choices could prepare them for more than one outcome.
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Why does foresight matter in the age of AI?
AI is already in use, but its longer-term implications remain uncertain. The OECD notes: “While artificial intelligence (AI) is already widely used today, the long-term implications of rapidly advancing AI systems remain largely unknown.” That uncertainty makes it important to consider not only how to use AI today, but also how different developments could affect future plans.
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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Foresight can help organizations examine possible changes and ask what they would mean for decisions made now. The OECD describes its purpose as building the capacity to explore and prepare for “multiple plausible futures and associated opportunities and challenges,” and to assess whether strategies are future-ready. That is a preparation exercise, not a promise that any scenario will come true.
How can AI help with scenario planning?
A joint OECD and World Economic Forum report published on 19 November 2025 examined AI use in strategic foresight through a global survey of 167 practitioners from government, business, academia, and civil society. The report says most surveyed foresight professionals use AI to scan for signals of change, analyse large datasets, and support scenario development.
Many respondents reported time savings and expanded analytical capacity. A smaller, growing group was experimenting with AI as a creative or analytical partner in systems mapping and scenario design. The report’s abstract gives no percentage for “most,” or quantified amount for time saved, so these findings should be read qualitatively—not as precise estimates or evidence that every organization uses AI this way.
These uses suggest how AI may support parts of foresight work: processing information at scale, helping surface signals, and assisting with scenario development. The survey describes practitioner experience; it does not establish that AI-supported foresight leads to better decisions or outcomes.
What can go wrong when AI is used for foresight?
The same OECD–WEF report identifies concerns about reliability, transparency, and bias, alongside gaps in technical skills and uneven access. Public-sector practitioners may face particular constraints related to data security and unclear guidance.
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Those concerns shape how AI should be used in foresight. AI may expand research capacity, but people still need to assess the material it produces, protect sensitive information, and retain responsibility for interpretation and decisions. If a scenario is based on weak or biased inputs, or its assumptions are unclear, additional analytical capacity alone does not make the scenario dependable.
What skills do people need in the age of AI?
AI literacy and foresight are complementary rather than interchangeable. AI literacy supports informed, critical, and responsible engagement with AI. Strategic foresight supports thinking about uncertainty, alternative futures, and preparations that can be made now.
In practice, an organization can bring both perspectives to a decision: assess the AI tools and outputs involved, then consider how changing conditions could affect the decision and what options would remain useful across plausible futures. That is a practical synthesis of the two capabilities, not proof that any single method guarantees a better result.
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Evidence supports the relevance of foresight as preparation under uncertainty, but does not show that it is universally absent or the single capability missing from the AI age. The OECD guidance cited here is framed for public policy; its methods may also be useful in business, but their effectiveness across sectors is not established by the cited material.
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