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

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.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.03.187
Primary Topic
Construction Project Management and Performance
Type
article
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article

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

Meruyert Kussaiyn, Timur Narbaev, Bakhtiyar Sultan
Procedia Computer Science
Construction Project Management and Performance
article

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

Meruyert Kussaiyn, Timur Narbaev, Bakhtiyar Sultan
article en

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.

Procedia Computer ScienceVol. 278
Kazakh-British Technical University (KZ), Politecnico di Torino (IT), Satbayev University (KZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Construction Project Management and Performance
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A dark side of artificial intelligence in projects: Preliminary insights from the consulting industry — Meruyert Kussaiyn, Timur Narbaev, et al. · Procedia Computer Science (2026) | TGRS Research Map | TGRS