The challenges of AI implementation in the public sector. An in-depth case studies analysis

Abstract

Time is now mature for researching AI implementation in the public sector, creating knowledge from real-life settings. The current paper goes in this direction, aiming to explore the challenges public organizations face in implementing AI. The research has been conducted through eight in-depth case studies of AI solutions. As a theoretical background, we relied on a framework proposed by Wirtz et al. [36] that identified four classes of challenges: AI Society, AI Ethics, AI Law and Regulations, and AI Technology Implementation. Our results first confirm the importance of the four classes of challenges. Second, they highlight the need to add a fifth class of challenges, i.e., AI Organizational change. In fact, public organizations are facing important challenges in settling AI solutions in daily operations, practices, tasks, etc. Finally, the five classes have been discussed, including more detailed insights extracted from the coding of the cases.