The aim of this paper is investigating the impact of artificial intelligence on the spend classification performed by a buyer firm. The information processing theory is the overarching structure of the study, identifying the information processing needs and capabilities underlying the use of artificial intelligence for spend classification. The case study methodology involves the IT providers currently offering AI-based spend classification solutions as privileged respondents. The unit of analysis is the AI-based spend classification solution offered by the IT provider and the relationship that is triggered between the IT provider delivering the solution and the buyer firm implementing it. Information processing needs in spend classification are high for buyer firms. Often, they are not supported by internal information processing capabilities. AI-based solutions offered by IT providers for spend classification compensate for the lacking capabilities of the buyer, enabling the fit between information processing needs and capabilities. The study of the information processing theory to the specific case of artificial intelligence in spend classification is novel, extending the application of the theory to a new context. This research contributes through the structuring of a phenomenon that is still not very common in firms and not widely studied scientifically.
