Generative Artificial Intelligence Governance in Procurement: Skills Transformation, Decision-Making Accountability and Ethical Issues

This article analyzes the impact of generative artificial intelligence on the procurement function, starting from two converging directions: the operational and strategic transformation of procurement through GenAI, and the ethical issues generated by its use in processes involving suppliers, commercial data, contracts, and decisions with economic or legal effects. The paper proposes an integrated analytical framework in which GenAI is examined simultaneously as an efficiency-enhancing technology, a cognitive augmentation tool, and a source of organizational risk. The study adopts an empirical qualitative design based on an open-ended questionnaire completed by 40 professionals from procurement, IT, legal, compliance, and retail/supply chain, analyzed through reflexive thematic analysis. The findings show that GenAI is valued mainly for preparatory, document-intensive tasks, while respondents reject its use for autonomous decisions with legal or economic effects; confidentiality, hallucinations, and diffuse accountability emerge as the dominant concerns. Building on these findings, the paper proposes a risk-tiered governance matrix that links GenAI use cases to control mechanisms and professional competences. The results indicate that the responsible adoption of GenAI depends less on the isolated technical performance of tools and more on the existence of an institutional architecture combining data quality, human oversight, auditability, protection of confidential information, and continuous professional training. The main conclusion is that the future of GenAI-assisted procurement should not be built on replacing the human decision-maker, but on controlled human–AI collaboration, in which generative systems support analysis while decision-making responsibility remains clearly allocated to the organization and its professionals.