@article{Zulnorain_2026, title={Algorithmic Governance and Trust Calibration in Project Management}, volume={12}, url={http://dx.doi.org/10.22161/ijaems.124.3}, DOI={10.22161/ijaems.124.3}, abstractNote={<jats:p>Today, AI and predictive analytics can obsolete the primitive “take a stab at it” attitude towards project risk management. These technologies ensure that the businesses are aware of building projects which may be delayed or cost overruns in advance. Most of the existing research however focuses on enhancing the math’s and algorithms and has not studied the question of trust and usage of this data amongst real project managers (PMs) working in their day to day role. This paper does so. We combine the Technology Acceptance Model (TAM) with Sociotechnical Systems (STS) theory to describe the human aspect of the AI tools. We argue that there are two problems with an out-of-balance manager’s trust: either the manager appeals to the wrong data (automation rejection) or the manager hands over to the machine, believing that the machine is always in the right (automation bias). Both the errors negatively affect the successful completion of a project.</jats:p>}, number={4}, journal={International Journal of Advanced Engineering, Management and Science}, publisher={AI Publications}, author={Zulnorain, Syed Osman}, year={2026}, pages={030–037} }