Enhancing Project Management Decision-Making with Explainable Artificial Intelligence (XAI): A Model for Transparency and Trust

Abstract

The study aims to understand the way in which Explainable Artificial Intelligence (XAI) is enhancing decisions made in the process of project management. It was a quantitative and research design where a structural survey tool using a validated scale was used to measure key constructs of study XAI, trust, understanding and quality of decision-making. The 233 samples were selected through an online questionnaire that was sent to experienced project managers who operate in fields of technology, construction, healthcare and financial aspects of different industries. The analysis of data employed structural equation modeling in the framework of SmartPLS software. The findings suggest that XAI considerably improves trust and understanding among project managers, which further boosts the quality of decision-making processes. To be more precise, path analysis revealed that the coefficient between XAI and trust ([Formula: see text]), XAI and understanding ([Formula: see text]), trust ([Formula: see text]) and understanding ([Formula: see text]) and quality of decisions was high and positive. Combined, they comprised 53% of the variance in the quality of decisions and this implies the mediating influence of the latter. Current research allows introducing findings that are considered a contribution to the current corpus of knowledge because they empirically prove the significance of XAI as a method of creating grounds of trust and comprehension within the project management environment.

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