The Role of Artificial Intelligence in Regulatory Decision-Making: Current Applications, Future Potential, and Implications for Expedited Review Processes

Abstract

This review examines the role of artificial intelligence (AI) in contemporary regulatory decision-making across pharmaceutical regulation, financial supervision, and public-sector governance. Drawing on peer-reviewed literature and regulatory guidance published between 2018 and 2025, this paper analyzes how AI technologies, including machine learning, natural language processing, predictive analytics, and explainable AI, are being integrated into regulatory workflows to support dossier review, pharmacovigilance, compliance monitoring, and risk-based oversight. Using a structured narrative review approach aligned with PRISMA 2020 principles, the study synthesizes evidence on current applications, efficiency gains, and institutional impacts of AI-enabled regulation. The analysis highlights documented improvements in review timelines, analytical consistency, and early risk detection, while critically examining persistent challenges related to explainability, algorithmic bias, data governance, accountability, and cross-jurisdictional harmonization. The review emphasizes that AI delivers the greatest regulatory value when implemented as decision-support within clearly defined governance frameworks rather than as an autonomous decision-maker. It argues that sustainable adoption depends on lifecycle oversight, transparency, human-in-the-loop safeguards, and international coordination of standards. By integrating insights across regulatory domains, this work contributes to the evolving field of regulatory science and provides evidence-based recommendations for responsible AI deployment without compromising legal accountability, public trust, or ethical safeguards.

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