Implementing agentic AI in project management: an evidence-based framework and maturity model from systematic analysis

Purpose This study develops an evidence-based implementation framework and maturity model for organizations adopting agentic artificial intelligence (AI) in project management, synthesizing insights from academic research and industry implementations. Design/methodology/approach Following PRISMA 2020 guidelines, we systematically reviewed 97 sources spanning 2019–2025, including 52 peer-reviewed articles and 45 rigorously screened gray literature sources (industry reports, technology documentation and professional body publications) across construction, software development and other sectors. Findings We identify five levels of AI autonomy currently deployed in practice, three dominant implementation pathways and critical success factors including data infrastructure readiness, organizational change capacity and governance mechanisms. Organizations report 30–50% productivity improvements, though quantified cost-reduction data remain notably absent from the published literature, suggesting either competitive sensitivity or measurement challenges in this emerging field. Research limitations/implications The evidence base is dominated by recent publications (65% from 2024–2025) and gray literature (41%), which limits the generalizability and durability of the findings. Quantified cost-reduction data specific to agentic AI are entirely absent from published sources. Future research should prioritize controlled empirical studies comparing agentic and traditional project management approaches, longitudinal tracking of human–AI team evolution, cross-cultural adoption studies and development of standardized reporting frameworks for agentic AI implementations. Practical implications The study provides: (1) a maturity assessment tool for organizational readiness, (2) an implementation roadmap with phase-gates and risk mitigation strategies, (3) a governance framework for human–AI collaboration and (4) an organizational performance measurement framework with validated Key Process Indicators (KPIs). Originality/value This is the first comprehensive analysis specifically focused on agentic AI in project management, providing actionable frameworks tested across multiple industries. The maturity model and implementation pathways offer immediate business value for organizations navigating AI transformation.