Towards Intelligent Project Management in the Finance Sector: A Scoping Review of AI Use Cases

Abstract

The integration of Artificial Intelligence (AI) into Project Management (PM) is gaining momentum as organisations seek more adaptive tools to manage complexity in the industry 4.0 era. While traditional methods like Gantt Charts and Earned Value Management (EVM) remain important, they are often inadequate for handling real-time data, predictive insights, and automated decisions. Emerging AI techniques including Large Language Models, Natural Language Processing, Artificial Neural Networks, and Fuzzy Bayesian Networks offer promising capabilities for enhancing planning accuracy, resource optimisation, risk detection, and communication. This scoping review maps the current applications of AI in project management, particularly during the planning and monitoring phases. Twenty-four peerreviewed articles ($2023-2025$) were selected from major databases including Scopus, Web of Science (WoS), IEEE Xplore, and Google Scholar. A bibliometric analysis was conducted to map the structure of the knowledge base and identify dominant AI techniques, thematic clusters, and their alignment with key project management functions. The findings highlight the growing use of AI in intelligent scheduling, dynamic resource allocation, and automated documentation. LLMs and NLP show strong potential for improving communication and reporting workflows. Despite these advances, challenges remain around data quality, AI readiness, and the absence of standardised frameworks. To address these gaps, future work will involve interviews with finance-sector project managers and the co-development of a tailored AI integration framework. This review provides a foundational understanding to support responsible and scalable AI adoption in project environments.