Current state of AI Adoption in Swedish Banks: Rationales, Challenges, and Lessons Learned

Sammanfattning: The field of Artificial Intelligence (AI) continues to revolutionise numerous sectors, and the banking industry is no different. This study investigates the rationales, challenges, and lessons learned from AI incorporation within Sweden's banking system. The research's objective is to elucidate the AI integration process and offer valuable guidance to organisations considering a similar technological transition. The research methodology is qualitative, primarily using comprehensive interviews with representatives from the banking sector and AI and computational linguistics experts. The study has successfully identified and categorised the reasons behind AI adoption, the primary challenges encountered during the integration process, and key learnings, which could prove beneficial for banks planning to incorporate AI into their operations. The findings indicate a somewhat paradoxical situation: despite a broad sense of optimism and expectation for AI becoming a core component in banking, the current integration rate is modest. This slow adoption rate can primarily be attributed to challenges such as data security, regulatory constraints, issues with data readiness, and the dynamic nature of AI technology. As a result, banks seem to be exercising caution, avoiding premature or extensive AI adoption.