GENERATIVE AI IN PROJECT MANAGEMENT: ENHANCING EFFICIENCY AND FINANCIAL PERFORMANCE

Abstract

Project management continues to face a high level of failures due to budget overruns, schedule delays, and insufficient quality, which directly cause financial inefficiency. This study examines how generative artificial intelligence (AI) can improve both operational and financial performance in project management. The purpose is to assess the impact of AI on efficiency with a focus on financial outcomes, evaluated through cost control, deadline compliance, and quality of deliverables.The methodology combines a literature review, scenario modeling across IT, construction, consulting, education, and research projects, and a comparative assessment using fuzzy logic to address uncertainty. In addition to operational aspects, financial indicators such as ROI, cost variance, and frequency of budget overruns were analyzed.The results show that generative AI improves efficiency across all life cycle phases. AI can reduce execution time by 10–15%, decrease budget deviations by 10–20%, and enhance quality through automation, advanced forecasting, and optimized resource allocation. Financial effects are most visible in knowledge-intensive projects (IT, consulting), where AI supports data-driven decision-making, accurate financial planning, and higher ROI. In construction, improvements are moderate, mainly through risk mitigation and planning accuracy.Findings confirm that AI does not replace classical methodologies (Agile, Waterfall) but strengthens them by improving financial discipline and compensating for weaknesses. For effective adoption, organizations must consider industry specifics, invest in staff training, and ensure reliable data and risk management. Generative AI emerges as a strategic driver of financial efficiency and competitive advantage in project management.