Issue Using generative AI to speed up foresight while keeping expert validation

Summary

One reason Korean foresight fails to reach policy is that fast-moving agendas leave no time to use research results at the right moment. The author sees generative AI as a way to strengthen the link, especially in demand-driven systems such as Foresight on Demand. AI can take over repetitive work like literature review, signal detection and drafting that used to take experts several weeks, shortening projects and freeing researchers for higher-level judgment. In data-based systems like Singapore's, it can also help interpret horizon scanning results and derive policy implications for rapid decisions. However, its use should be treated as a process-design question, with scope set by client needs, careful prompt design and expert validation to offset data bias and weak explainability. The author frames generative AI as complementary infrastructure for strategic decisions rather than a substitute for futures research.