Artificial Intelligence in Procurement : Leveraging Google Gemini to Improve the Purchasing Process
Year: 2025
Type: dissertation
Abstract: This study explores the application of Google Gemini AI within the technical services purchasing process at a case company. The procurement department at the case company has identified a growing need to explore and implement AI-driven solutions to improve the efficiency and quality of its operations. While a growing body of literature demonstrates the potential of AI to enhance various facets of the purchasing process, research in this area is still developing. This research employs a design research approach, integrating Lean Six Sigma methodology, and uses data collected through observations, documentation, and workshops. The analysis includes lead time and defect measurements from five runs for each pilot case, comparing old and new process designs. Findings indicate that Google Gemini can reduce lead times for PO text and RFQ text generation; however, it also introduces challenges, including difficulties in adhering to templates and ensuring output consistency. The study reveals that while AI offers potential for efficiency gains in procurement, current limitations necessitate careful consideration of its implementation and continued development.
Source: Osuva (University of Vaasa)
Author: Kastari, Lassi Pekka
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6980060800