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AI meets spend classification: A new frontier in information processing

Michela Guida et al.

Journal of Purchasing and Supply Management2025https://doi.org/10.1016/j.pursup.2025.100993article
AJG 3ABDC A
Weight
0.52

Abstract

This paper investigates the impact of artificial intelligence (AI) on spend classification in buyer firms, using the organizational information processing theory (OIPT) as a reference framework. Existing research on the use of AI in procurement lacks a holistic approach that effectively integrates human oversight. This gap is particularly evident in procurement activities beyond automating repetitive tasks, especially in advanced analyses supporting strategic purchasing decisions, such as spend classification. Through a case study approach focusing on providers of AI-based spend classification solutions, this research highlights how AI addresses the substantial information processing needs that exceed the internal capabilities of buyer firms. By aligning these needs with the capabilities enabled by the adoption of AI, the study demonstrates a significant advancement in spend classification practices. This research applies the theoretical constructs of the OIPT at the intersection of two relatively unexplored domains—spend classification and AI and aims to translate these constructs into actionable insights for professionals, thereby making a significant contribution to the field. • The paper examines the impact of artificial intelligence (AI) on spend classification within buyer firms, using the information processing theory as its framework. • It employs a case study methodology involving IT providers offering AI-based spend classification solutions. • Buyer firms often face information processing needs in spend classification beyond their internal capabilities, which AI solutions provided by IT providers aim to address. • This study presents a novel application of the information processing theory to AI in spend classification, contributing valuable insights to this relatively unexplored domain.

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https://doi.org/https://doi.org/10.1016/j.pursup.2025.100993

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@article{michela2025,
  title        = {{AI meets spend classification: A new frontier in information processing}},
  author       = {Michela Guida et al.},
  journal      = {Journal of Purchasing and Supply Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.pursup.2025.100993},
}

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Evidence weight

0.52

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.47 × 0.4 = 0.19
M · momentum0.68 × 0.15 = 0.10
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.