Policy-aligned Research Trajectories in AI-Enabled Clinical Trials: A 2015–2025 Bibliometric Synthesis and Governance Implications for Korea and the UK

Introduction Artificial intelligence (AI) has become a key driver of innovation in clinical research and public health. This study aimed to identify policy-aligned research trajectories in AI-enabled clinical trials in Korea and the United Kingdom from 2015 to 2025. Methods A bibliometric synthesis was conducted using the Web of Science Core Collection to analyze publication trends, research domains, and institutional networks. Policy alignment was assessed through qualitative mapping of national strategic documents from both countries, including Korea’s Ministry of Health and Welfare R&D Implementation Plans and the UK’s MRC and NIHR strategies. Results In this study, we analyzed 925 publications to examine trends in AI-enabled clinical trial research in Korea and the UK. Publication activity increased steadily in both countries. Korean studies most often applied AI to outcome analysis and data integration, whereas research from the UK covered a broader set of trial stages, including design, recruitment, and monitoring. We also observed differences in collaboration patterns, with Korean research activity concentrated in university hospitals and UK research distributed across NHS trusts and research institutes. When these findings were compared with national policy documents, both countries showed overlapping priorities related to digital health, real-world data use, and international research collaboration. Discussion Based on these results, we interpret the research landscapes of Korea and the UK as exhibiting complementary strengths in AI-enabled clinical trial research. Korea’s emphasis on outcome-oriented applications contrasts with the UK’s engagement across multiple trial stages. We view these differences as indicating areas where coordination could be explored, particularly in relation to interoperability, data sharing, and trial efficiency, without implying established governance outcomes. Conclusion By integrating bibliometric evidence with policy analysis, we provide a comparative overview of AI-enabled clinical trial research in Korea and the UK. We interpret the findings as a basis for informing future discussions among researchers and policymakers about collaborative governance approaches in this field, within the scope of the study’s methodological limitations.