In the face of increasing project uncertainty, organizations are turning to artificial intelligence (AI) to enhance their project management (PM), including project forecasting, resource allocation, and risk management. However, the effectiveness of such solutions depends on AI transparency, user trust, and the ability to adapt to complex and changing conditions. This study examines the dark side of AI in PM and is based on interviews with experienced project managers and a survey of employees of a consulting organization in Kazakhstan. It finds a weak positive correlation between perceptions of AI efficiency and AI transparency (r = 0.2342), as well as no statistically significant differences in perceptions of AI transparency across professionals with different experience levels. The most critical risks were AI-driven errors (58.8% of the respondents), low transparency (49.0%), and low work efficiency (41.2%). Also, 31.4% of participants expressed concerns about biased decisions and the need for manual corrections of AI-driven decisions. These results confirm that without explainability mechanisms and ongoing human oversight, AI may not reduce risks but can actually exacerbate them. This preliminary study highlights the need for further cross-industry and larger-scale empirical studies.

A dark side of artificial intelligence in projects: Preliminary insights from the consulting industry / Narbaev, T., Kussaiyn, M., Sultan, B.. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - 278:(2026), pp. 1918-1925. (International Conference on ENTERprise Information Systems, CENTERIS 2025, International Conference on Project MANagement, ProjMAN 2025, International Conference on Health and Social Care Information Systems and Technologies, HCist 2025 Abu Dhabi 2025) [10.1016/j.procs.2026.03.187].

A dark side of artificial intelligence in projects: Preliminary insights from the consulting industry

Narbaev T.;
2026

Abstract

In the face of increasing project uncertainty, organizations are turning to artificial intelligence (AI) to enhance their project management (PM), including project forecasting, resource allocation, and risk management. However, the effectiveness of such solutions depends on AI transparency, user trust, and the ability to adapt to complex and changing conditions. This study examines the dark side of AI in PM and is based on interviews with experienced project managers and a survey of employees of a consulting organization in Kazakhstan. It finds a weak positive correlation between perceptions of AI efficiency and AI transparency (r = 0.2342), as well as no statistically significant differences in perceptions of AI transparency across professionals with different experience levels. The most critical risks were AI-driven errors (58.8% of the respondents), low transparency (49.0%), and low work efficiency (41.2%). Also, 31.4% of participants expressed concerns about biased decisions and the need for manual corrections of AI-driven decisions. These results confirm that without explainability mechanisms and ongoing human oversight, AI may not reduce risks but can actually exacerbate them. This preliminary study highlights the need for further cross-industry and larger-scale empirical studies.
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3015487
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