Artificial intelligence (AI) and machine learning (ML) in procurement and purchasing decision-support (DS): a taxonomic literature review and research opportunities

Artificial intelligence (AI), machine learning (ML) and decision-support (DS) are gaining increasing interest with widening adoption. This article investigates the enabler role of AI and ML for providing decision-support in procurement&purchasing domain. The study follows a systematic review approach via taxonomic analysis. Comprehensive analysis and discussions are provided for: (a) the relevance and applicability of AI and ML in procurement&purchasing decision-support; (b) functionalities/processes for which they are utilized; (c) related methodologies; and (d) implementation benefits as well as challenges. Findings reveal that procurement&purchasing area holds significant potential in terms of AI-ML applications for decision-support almost every related sub-process. This study is original by offering a process-oriented approach to the research domain; providing unique clustering and classification; and presenting detailed analyses via unique taxonomy tables with respect to approach, topic, focus, context and methodologies of the literature items reviewed. The study offers further research opportunities and has significant potential to provide managerial insights by the identified sectoral applications, benefits and challenges.

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Publication Details

Journal
Artificial Intelligence Review
Published
2025-08-20
DOI
https://doi.org/10.1007/s10462-025-11336-1
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57
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article

Artificial intelligence (AI) and machine learning (ML) in procurement and purchasing decision-support (DS): a taxonomic literature review and research opportunities

Dursun Balkan, Göknur Arzu Akyüz
2 citations
Artificial Intelligence Review
Big Data and Business Intelligence
4.57
article

Artificial intelligence (AI) and machine learning (ML) in procurement and purchasing decision-support (DS): a taxonomic literature review and research opportunities

Dursun Balkan, Göknur Arzu Akyüz
article en
2 citations

Abstract

Artificial intelligence (AI), machine learning (ML) and decision-support (DS) are gaining increasing interest with widening adoption. This article investigates the enabler role of AI and ML for providing decision-support in procurement&purchasing domain. The study follows a systematic review approach via taxonomic analysis. Comprehensive analysis and discussions are provided for: (a) the relevance and applicability of AI and ML in procurement&purchasing decision-support; (b) functionalities/processes for which they are utilized; (c) related methodologies; and (d) implementation benefits as well as challenges. Findings reveal that procurement&purchasing area holds significant potential in terms of AI-ML applications for decision-support almost every related sub-process. This study is original by offering a process-oriented approach to the research domain; providing unique clustering and classification; and presenting detailed analyses via unique taxonomy tables with respect to approach, topic, focus, context and methodologies of the literature items reviewed. The study offers further research opportunities and has significant potential to provide managerial insights by the identified sectoral applications, benefits and challenges.

Artificial Intelligence ReviewVol. 58(11)
University of Turkish Aeronautical Association (TR), Gazi University (TR)
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Big Data and Business Intelligence
4.57
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Artificial intelligence (AI) and machine learning (ML) in procurement and purchasing decision-support (DS): a taxonomic literature review and research opportunities — Dursun Balkan, Göknur Arzu Akyüz · Artificial Intelligence Review (2025) | TGRS Research Map | TGRS