Key-Challenges of Public Procurement of AI in the Swedish Public Sector : Case study at IBM with a focus on NLP Technologies

University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

Abstract: The economic potential in introducing Artificial Intelligence (AI) into the Swedish Public administration is substantial and it is calculated to be approximately 140B SEK per year[5]. However, without a comprehensive AI strategy and lack of sufficient digital competence, an AI implementation becomes a struggle [9]. According to IBM Research, 120 million people around the world admitted that they may need to upskill due to automation and AI, which has aggravated during the pandemic. However, the lack of digital skills is the biggest barrier to this process. This study analyzes the challenges of an application of the AI technology, Natural Language Processing (NLP), in public procurement. Through a qualitative method with an abductive approach, 10 semi-structured interviews are conducted with experts from the public- and private sector and identify key challenges of NLP in public procurement which are the lack of digital skills, legal-, ethical- and organizational challenges of NLP in the public context and the public sector’s inability to create partnerships and use business networks. This thesis is a case study of IBM that contributes to research on AI in the public sector and aims to help fill the research gap that exists within this field. The study’s purpose is to analyze and provide better insight into public procurement of NLP to increase the use of NLP technologies within public administration in Sweden. 

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