Artificial Intelligence in Policymaking: Mapping Integration Gaps Across the Public Policy Cycle

Abstract

Governments worldwide are increasingly exploring the use of Artificial Intelligence (AI) to support and transform policymaking. Despite the growing number of national AI strategies and initiatives, systematic evidence on how AI is integrated across the stages of the policymaking process remains limited. This lack of clarity risks fragmented integration and slows the diffusion of effective practices. This study addresses this gap by examining how AI-enabled policy actions are incorporated into policymaking processes across eight European countries. We analyze policy documents to identify AI-enabled policy actions and map them across the phases of the public policy cycle. The analysis reveals 33 AI-enabled policy actions and reveals uneven integration across policy stages and countries. While several actions focus on data infrastructure, digital public services, and agenda setting, considerably fewer initiatives target implementation monitoring, evaluation, and responsibility-related governance mechanisms. The study contributes to the literature by (1) systematically mapping AI-enabled policy actions across the policy cycle, (2) identifying integration gaps in current policymaking practices, and (3) outlining eight directions for future research.