In recent years artificial intelligence (AI) has been seen as a technology with tremendous potential for enabling companies to gain an operational and competitive advantage. However, despite the use of AI, businesses continue to face challenges and are unable to immediately realize performance gains. Furthermore, firms need to introduce robust AI systems and mitigate AI risks, which emphasizes the importance of creating suitable AI governance practices. This study, explores how AI governance is applied to promote the development of robust AI applications that do not introduce negative effects, based on a comparative case analysis of three firms in the energy sector. The study illustrates which practices are placed to produce knowledge that assists with decision making while at the same time overcoming barriers with recommended actions leading to desired outcomes. The study contributes by exploring the main dimensions relevant to AI’s governance in organizations and by uncovering the practices that underpin them.

In recent years artificial intelligence (AI) has been seen as a technology with the potential for significant impact in enabling firms to get an operational and competitive advantage. However, despite the use of AI, companies still face challenges and cannot quickly realize performance gains. Adding to the above, firms need to introduce robust AI systems and minimize AI risks, which places a strong emphasis on establishing appropriate AI governance practices. In this paper, we build on a single case study approach and examine how AI governance is implemented in order to facilitate the development of AI applications that are robust and do not introduce negative impacts to companies. The study contributes by exploring the main dimensions relevant to AI's governance in organizations and by uncovering the practices that underpin them.