Towards artificially intelligent procurement

Hadia Nadeem

This PhD project investigates the adoption of Artificial Intelligence in procurement organizations focusing on how this emerging technology transforms procurement processes, decision-making, and organizational efficiency. As AI adoption in business continues to accelerate, procurement organizations are uniquely positioned to benefit from automation, predictive analytics, and machine learning, which can enhance supplier selection, risk management, and contract management. The research question is: What are the factors influencing the adoption and effective implementation of AI in procurement organizations?

The study uses a mixed-methods approach, involving both qualitative interviews with procurement managers and quantitative analysis of procurement performance data from multiple large organizations. The first phase is guided by qualitative interviews within a procurement team at a large fashion retailer in Sweden and will be followed by a second phase based on quantitative methods. This empirical approach allows for an in-depth exploration of barriers, drivers, and organizational outcomes associated with AI adoption. The theoretical framing draws on sensemaking theory, technology acceptance models (TAM) and the resource-based view (RBV), providing a lens to examine both individual and organizational readiness for AI. Preliminary findings from a longitudinal study indicates that while AI adoption promises efficiency gains, challenges such as data quality, change management, and integration with existing systems remain significant barriers/challenges.

The project is part of a wider research project on AI as a new strategic imperative funded by the Marianne and Marcus Wallenberg foundation (grant number MMW 2019.0251 WASP-HS).