Artificial Intelligence in Project Management: Challenges, Strategies and Best Practices [version 2; peer review: 1 approved, 2 approved with reservations]

The application of Artificial Intelligence (AI) in project management is transforming decision-making processes, enhancing task execution, and improving risk management. This study aimed to elucidate the challenges raised by AI in project management (PM) using a scientometric and qualitative analysis. The research employs both quantitative and qualitative analysis using VOSviewer. The scientometric analyses reveal a substantial increase in AI in PM publications, with “project management,” “artificial intelligence,” “machine learning,” “cost reduction,” “decision making” and “supply chain management” as the most influential co-occurrence. The systematic review the implementation of challenges and strategies. The analysis identifies the publication trends, most significant keywords, leading institutions and researchers, prominent collaboration connections, primary publication venues, and the most-cited publications. This research enhances understanding of AI in PM, promotes the utilization of artificial intelligence technologies for gaining insights during certain phases of project development, and improves project management efficiency. The utilization of AI technologies, including machine learning, natural language processing, and predictive analytics, markedly improves project efficiency by enhancing decision-making, effectiveness, and risk mitigation. The recent rise of agentic and generative AI systems is transforming the role of AI in project environments from passive analytical support to active decision augmentation and workflow orchestration. Simultaneously, agentic AI systems, which are autonomous or semi-autonomous digital agents proficient in planning, performing activities, and engaging with various project data sources. These advancements indicate a shift from AI as a predictive instrument to AI as a collaborative cognitive framework within project ecosystems, prompting new inquiries on governance, accountability, and human-AI collaboration in project decision-making.