Artificial intelligence in procurement: a systematic and AI-assisted literature review

Purpose This study investigates the application of artificial intelligence (AI) within global procurement processes. It builds upon prior literature and offers novel methodological insights while pinpointing trends and outlining research gaps for future investigations. Design/methodology/approach The study combines a bibliometric literature review using VOSviewer with an AI-assisted review process. AI tools, including ChatGPT, are integrated into selected stages of the review and examined alongside researcher-driven approaches to assess their usefulness and limitations in supporting systematic literature analysis. Findings The results indicate a shift in AI use in procurement from isolated automation toward more strategic integration. The literature increasingly focuses on strategic areas such as supplier management, while comprehensive implementation frameworks remain limited. The analysis of AI-assisted reviewing suggests that such tools can support efficiency and consistency, but their application remains sensitive to conceptual ambiguity and requires human oversight, particularly in classification tasks. Originality/value This study offers two distinct contributions to the literature. First, it provides a focused analysis of how research on AI in procurement has evolved since previous systematic literature reviews (SLRs), emphasising studies that examine real-world implementation and effectiveness rather than merely discussing willingness or barriers to adoption. Second, it provides an exploratory assessment of AI-assisted reviewing as an emerging methodological approach, highlighting both its potential and its current limitations.