Artificial Intelligence in Project Management: Challenges, Strategies and Best Practices

Area of Science:

• Project Management
• Artificial Intelligence
• Information Science

Background:

• Artificial Intelligence (AI) is increasingly integrated into project management (PM).
• AI applications enhance decision-making, task execution, and risk management.
• Recent advancements include agentic and generative AI systems.

Purpose of the Study:

• To analyze the challenges and trends of AI in project management.
• To identify key research areas, influential publications, and collaborations.
• To understand the evolving role of AI from analytical support to cognitive frameworks.

Main Methods:

• Scientometric analysis using VOSviewer.
• Qualitative analysis of AI in PM literature.
• Systematic review of implementation challenges and strategies.

Main Results:

• Significant growth in AI in PM publications.
• "Project management," "artificial intelligence," and "machine learning" are key co-occurring terms.
• Identified publication trends, leading institutions, and influential keywords like "cost reduction" and "decision making."

Conclusions:

• AI, including machine learning and predictive analytics, improves project efficiency and risk mitigation.
• Agentic AI represents a shift towards active decision augmentation and workflow orchestration.
• Emerging AI capabilities necessitate new considerations for governance, accountability, and human-AI collaboration in project ecosystems.