THE USE OF ARTIFICIAL INTELLIGENCE IN IT PROJECT MANAGEMENT IN THE CONTEXT OF DIGITALIZATION

Abstract

Introduction. In the context of rapid digitalization, almost all areas of activity are undergoing profound transformations driven by the adoption of advanced information technologies. These changes are particularly dynamic in IT project management, where decision-making speed, adaptability, efficient resource allocation, and risk management are critical success factors. In this regard, artificial intelligence (AI) is viewed not only as a tool for automating routine operations but also as a powerful driver for optimizing managerial decisions at all stages of the IT project life cycle. The emergence of intelligent systems capable of analysing large data sets, forecasting user behaviour, detecting hidden patterns, and supporting decision-making creates fundamentally new opportunities for enhancing management effectiveness. However, together with these opportunities arise new challenges, including the need to ensure transparency of decisions, address ethical dilemmas, and transform managerial approaches to align AI solutions with the organizational context. This underscores the need for systematic scientific research on the impact of AI on IT project management and the development of methodological foundations for its application in conditions of digital transformation.

Purpose. The purpose of this article is to investigate the role and potential applications of artificial intelligence in IT project management under digitalization. The study aims to analyse current practices of AI integration into management processes, assess the effectiveness of intelligent technologies for decision support, risk management, resource optimization, and quality improvement in IT project implementation. Another objective is to identify key challenges faced by managers during AI adoption and to formulate proposals for enhancing managerial approaches based on intelligent technologies.

Methods. The research employs methods of scientific literature analysis, comparison of contemporary practices of AI use in IT project management, and elements of systems analysis to identify key trends and challenges. The source base includes publications in scholarly journals, reports by international organizations, and case studies of AI implementation in the IT sector. A structural-logical approach was used to synthesize the results, enabling the identification of major directions of AI influence on managerial processes.

Results. The findings demonstrate that artificial intelligence plays an increasingly significant role in IT project management, contributing to improved efficiency, planning accuracy, and adaptability. AI implementation at the stages of initiation, planning, execution, and monitoring enables the automation of routine tasks, timely responses to deviations, and informed decision-making under constraints of time and resources. One of the key areas is the use of machine learning algorithms to analyse historical data, predict task duration, evaluate team workload, and identify potential risks. Intelligent decision-support systems help determine optimal actions in complex situations by accounting for numerous variables inherent in IT environments.

The application of advanced AI tools improves internal team communication, accelerates information processing, and reduces the likelihood of misunderstandings. Practical experience of companies using AI tools (ClickUp AI, Atlassian Intelligence, Microsoft Copilot) demonstrates shorter project duration, improved outcomes, and the formation of hybrid management models combining the structure of classical methodologies with the flexibility of Agile approaches. At the same time, AI integration is accompanied by challenges such as high data quality requirements, difficulties in adapting existing processes, insufficient staff readiness, and issues related to trust in automated decisions. Moreover, the role of the manager is shifting from coordinator to analyst and moderator of human–system interaction.

The results highlight the need for systematic integration of artificial intelligence into managerial frameworks, facilitating a transition toward analytical and adaptive models of IT project management.

Conclusions. The study establishes that the use of artificial intelligence in IT project management is a key factor in enhancing efficiency and adaptability in the context of digitalization. AI enables the automation of managerial processes, improvement of forecasting accuracy, reduction of risks, and strengthening of decision-making quality. The most effective AI applications include machine learning for performance analysis, predictive analytics for resource planning, and decision-support systems for complex environments. However, effectiveness depends on organizational readiness to modify internal processes, foster digital culture, and invest in human capital development. The study substantiates that AI acts not only as a technological tool but also as a catalyst for changes in managerial practices. Further research should focus on developing methodological approaches to AI integration in project management, taking into account organizational, ethical, and technical factors.

Keywords: artificial intelligence; IT project management; digitalization; machine learning; predictive analytics; managerial decision-making; digital transformation.

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