Journal of Global Economics, Management and Business Research

This article presents a narrative literature review of the emerging intersection between Generative Artificial Intelligence (GenAI) and Agile Project Management (APM). Using purposive, iterative searches across academic and practitioner sources, we screen for relevance to GenAI applications along the Agile lifecycle (planning, backlog refinement, estimation, development, testing, and retrospectives) and synthesize findings through a concept-centric, thematic analysis. The paper makes three contributions: (1) an integrative GenAI–APM alignment framework that maps core GenAI capabilities (e.g., requirements elaboration, code and test generation, risk sensing, knowledge summarization) to Agile roles, ceremonies, and artifacts; (2) an evidence-weighted assessment of opportunities (speed, decision support, collaboration) and risks (bias, privacy, model drift, over-reliance), with associated governance controls; and (3) a research agenda with testable propositions on effectiveness, human–AI teaming, measurement, compliance, and adoption barriers. Scholarly implications include clearer constructs and operational definitions to support cumulative empirical work. Practical implications include actionable guidance for PMOs and Scrum teams on where to pilot GenAI, how to measure value, and how to implement safeguards (data governance, responsible-AI checklists, and role/skill adjustments). By clarifying method, contribution, and significance, the review consolidates a fragmented discourse and offers a roadmap for rigorous research and responsible deployment of GenAI in Agile settings.