This dataset was curated specifically for the study presented in the paper, Decoding Development: The AI Frontier in Policy Crafting - A Systematic Review. It comprises 208 peer-reviewed publications that examine the integration of artificial intelligence (AI) and machine learning (ML) in policy planning and development. Each dataset entry includes detailed metadata, such as planning context, policy planning stage (e.g., problem diagnosis, resource allocation, outcome projection), specific Sustainable Development Goals (SDGs) addressed, and documented applications of AI/ML models. Systematically constructed, the dataset enables cross-sectional and comparative analyses, capturing the distribution and intensity of AI/ML applications across different stages of the policy planning cycle and economic contexts. By organizing data on each publication’s thematic focus and methodological approaches, this dataset facilitates a nuanced analysis of research trends, identifies existing gaps, and examines the role of smart algorithms in advancing development-oriented policy.