Generative AI in procurement

Abstract

The aim of the thesis was to determine where generative artificial intelligence (Gen AI) could be utilized as part of procurement operations, identify the types of AI solutions suitable for the case company, evaluate their benefits, and create a proof of concept for the company. The purpose of the thesis was also to serve as a starting point for the company’s transition into the AI era. The case company’s utilization of AI was in its early stages, and a new ERP system would enable a broader application of generative AI.

Qualitative research methods were employed in the study, and potential use cases for generative AI were mapped through a survey and a workshop. The survey identified the ten most beneficial applications. The use cases were then evaluated using the weighted sum method for multi-criteria decision-making as part of the existing procurement processes.

Generative AI can significantly enhance procurement processes. Its ability to summarize and create information has a productivity-enhancing effect. Gen AI significantly reduces the time used in order monitoring and can also improve the tendering process. Gen AI can help unexperienced Excel users while other applications can support work in different ways. The results can be applied to the procurement operations of other technology companies with similar procurement processes, as well as those using similar software. These applications can also be utilized in other operational areas of the case company.