When Machines Manage

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.4018/ijabim.384773
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

The study aims to investigate the adoption and impact of artificial intelligence (AI) in project management (PM) in Kazakhstan. One hundred fifty-nine experts from the academic and industrial sectors provided the survey data. Statistical methods, social network analysis, and analysis of variance were used to evaluate the significance of changes in the impact of AI, using a Tukey post-hoc test. The study results showed differences in the degree of AI adoption across eight PDs and the need for a customized approach to maximize the benefits of AI in PM. The research found that different PDs see different effects of AI on project success. Low technology readiness, financial constraints, and insufficient experience were the main barriers to effective AI adoption. This study offers practical recommendations for project-oriented companies implementing AI, thereby filling a gap in the literature by proposing PM as a new application area for dynamic models of human-machine interaction. Future studies should expand the geographic sample and add other factors influencing AI applications.