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.