Transforming Governance: A Systematic Review of AI Applications in Policymaking

Abstract

This systematic literature review examines the transformative applications of artificial intelligence (AI) in policymaking, exploring its potential to enhance decision-making, public engagement, and governance effectiveness. Employing a rigorous research methodology, this review analyzed scholarly articles from Scopus, Web of Science, and PubMed databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, ensuring methodological transparency and reproducibility. The final dataset of 22 articles was synthesized into four key themes: (i) AI in policy development and implementation, which focuses on data-driven decision support in policy formulation; (ii) AI in public administration and governance, highlighting AI’s role in improving public sector efficiency and resilience; (iii) ethical and regulatory aspects of AI in policymaking, which addresses critical issues like transparency, privacy, and bias; and (iv) applications of AI in specific policy domains, encompassing areas such as public health, environmental sustainability, and education. Findings indicate that AI can support evidence-based policymaking by facilitating real-time data analysis, scenario modeling, and enhanced public participation. However, challenges persist, particularly concerning ethical considerations, algorithmic accountability, and regulatory frameworks that ensure AI is implemented responsibly and equitably. This review underscores the need for interdisciplinary collaboration, ethical standards, and robust governance frameworks to address these challenges and maximize AI’s benefits in policy development and implementation. The synthesis of insights from diverse policy contexts provides a foundation for future research, encouraging exploration of responsible AI integration in policymaking to advance public trust, accountability, and policy effectiveness).