Conceptual Framework to Guide the Application of Artificial Intelligence in Project Management Decision Making

Abstract

Projects continue to fail despite technological advancements, with poor decision-making being a primary contributing factor. With the growing interest in Artificial Intelligence (AI) in project management (PM) and decision-making, AI could improve decision-making and project performance. However, to implement AI for this purpose, limited comprehensive guidelines and frameworks exist to assist project managers in identifying where to begin, which critical factors to consider, what changes or developments are necessary, and the specific expertise required. Therefore, this study explores the critical factors for implementing AI in project decision-making through a mixed-methods approach. Firstly, a semi-structured focus group interview was conducted with selected individuals from a project-based engineering firm. The thematic analysis of the qualitative data identified limitations in project success and decision-making, as well as implementation considerations for AI in project decision-making. Secondly, quantitative data was gathered using an online survey and analysed using descriptive statistics to rank the importance of the seven identified success groups and their factors. A conceptual framework was developed considering the importance of the seven success groups and their factors. This framework addresses the shortcomings of an existing model to guide the successful implementation of AI in PM to support and improve project decision-making and performance.

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