THEORETICAL ASPECTS OF PROJECT MANAGEMENT TRANSFORMATION IN THE IT SECTOR

Abstract

This article addresses the selection criteria for automating tasks in IT project management using artificial intelligence (AI). The rapid pace of digital transformation and increasing complexity of IT projects make it imperative for organizations to enhance their decision-making effectiveness and optimize project management processes. The research aims to scientifically substantiate criteria to evaluate the feasibility of automating specific managerial tasks within IT project management. The study identifies and analyzes five critical criteria: task repetition and regularity, low complexity and minimal expertise requirement, labor intensity, susceptibility to errors and the associated costs, and availability of sufficient data or clearly defined rules. Through methodological analysis and evaluation of contemporary practices, the article demonstrates that tasks meeting these criteria — such as routine report generation, data formatting, resource allocation, financial calculations, and predictive analytics — are optimal candidates for automation. The obtained results indicate substantial benefits from automation, including significant reductions in time and financial expenditures, minimized human error, enhanced accuracy in administrative tasks, and improved allocation of resources toward strategic initiatives. However, the study also highlights several challenges accompanying AI integration, such as data security risks, ethical considerations, algorithmic bias, and potential loss of managerial oversight due to excessive reliance on automated systems. The practical value of this research lies in providing IT project managers and organizational leaders with robust guidelines to strategically select tasks for automation. By clearly defining the criteria, the article enables organizations to avoid both under-automation, which fails to leverage available technologies, and over-automation, which could compromise operational oversight. Ultimately, effective automation informed by the identified criteria significantly boosts project management efficiency and organizational competitiveness.