Using Artificial Intelligence for Resource Forecasting in Strategic Project Management

Abstract

Aims: This study aims to evaluate the impact of artificial intelligence on project management processes, with a focus on resource forecasting. It further identifies key implementation challenges and provides strategic recommendations for effective AI integration. Study design: Analytical research based on secondary data and simulation modeling. Place and Duration of Study: The research was conducted through analytical evaluation of global scientific publications and applied modeling between January 2024 and February 2025. Methodology: The study applied an analysis of scientific literature to identify current trends in the use of artificial intelligence, a structural-logical method for generalizing forecasting processes, and machine learning-based simulation modeling to evaluate AI capabilities in project management. Comparative analysis and synthesis methods were used to develop practical recommendations, considering organizational, technical, and economic constraints. Results: The study revealed that artificial intelligence improves the accuracy of project resource forecasting, reduces the risk of exceeding budgets, and enhances adaptability to change. In particular, the use of machine learning reduced forecasting errors by up to 17% compared to traditional methods. Key implementation challenges were identified, including poor data quality, high implementation costs, and insufficient staff competencies. A phased approach to AI integration is proposed, including pilot project deployment, reliable data preparation, and targeted staff training. Conclusion: Artificial intelligence plays a critical role in enhancing the effectiveness of strategic project management by enabling more accurate forecasting, optimized resource allocation, and timely adaptation. Future research should focus on improving algorithmic accuracy, developing industry-specific AI models, and creating implementation standards to ensure long-term project sustainability and resilience. This article is important for the scientific community as it addresses a critical challenge in modern project management - the integration of artificial intelligence into resource forecasting. The review systematizes recent interdisciplinary findings and supports the development of advanced methodologies at the intersection of AI and strategic planning. It contributes to bridging theoretical knowledge and practical applications across various industries. The results may serve as a foundation for further research and innovation in digital project management.