Year: 2024
Type: dissertation
Abstract: This thesis explored the possibility of integration of Generative Artificial Intelligence (GenAI) into the public procurement process within the Helsinki Social Services, Health Care, and Rescue Services Division (SOTEPE). The objective of the thesis was to give recommendations for employing GenAI tools to help to optimize the public procurement process, thereby improving operational efficiency and reducing costs. \n \nThe research was structured in four stages: (1) current state analysis through department documentation review and stakeholder interviews; (2) a literature review to frame GenAI capabilities; (3) co-creation of initial recommendations with the stake-holders, via a workshop; and (4) validation of these recommendations with selected department leaders. Data collection was qualitative, focusing on interviews and participatory workshops to gather insights from the stakeholders. \n \nThe research identified non-productivity points related to time use, as well as to accuracy and quality of certain tasks in the current procurement practices. GenAI was found to be a viable solution to these non-productivity points due to its ability to assist in or to automate some of the tasks in the public procurement process, thus freeing up employee time for more strategic activities. \n \nThe outcome of the study was a set of recommendations on integrating GenAI into various stages of the public procurement process.
Source: Theseus (Ammattikorkeakoulujen)
Author: Rissanen, Toni
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7062741595