AI is beginning to reshape the entire policymaking cycle, from identifying problems to evaluating whether policies actually work. Governments can use AI to process huge volumes of public feedback, academic research, legal documents and policy reports, helping officials identify trends and understand complex problems more quickly.
The technology can also support policy choices through forecasting, simulation and geospatial analysis. Governments could model potential outcomes before adopting a policy, while geographic data can reveal where transport, schools, hospitals or social programmes are failing to reach people effectively. During implementation, AI can help target resources more precisely, and real-time dashboards can allow governments to evaluate programmes continuously rather than waiting until the end of a traditional policy cycle.
But the UNRIC analysis makes an important distinction: AI can support policymaking without becoming the policymaker. AI can identify patterns, generate forecasts and process information at a scale human teams cannot match, but it cannot determine what is fair, ethical or socially acceptable—and it cannot ultimately be held accountable for those decisions. Policymakers therefore need enough AI literacy to understand both the technology's capabilities and its limitations.
The broader takeaway is that AI literacy is becoming a core competency for government leaders, not merely a technical skill for engineers. The challenge is to integrate AI into public institutions while preserving human judgment, transparency, accountability and fairness. This is particularly important because existing governance systems were not designed for technology evolving at today's speed, creating an “evidence dilemma” in which regulation can struggle to keep pace with technological change.
