This study demonstrates that banking organizations with higher investments in AI technologies are exposed to more operational risk. Using comprehensive supervisory data on operational losses from large U.S. bank holding companies (BHCs) combined with detailed company-level data on AI-skilled human capital, we show that BHCs with more AI investments suffer higher operational losses per dollar of total assets. This relationship remains robust when using an instrumental variables (IV) approach based on BHCs' historical connections to universities with strong AI research programs. The impact of AI investment on operational losses significantly varies by loss type, being particularly driven by external fraud, client-related issues, and system failures. These losses stem not only from small, frequent incidents but also from severe, tail-risk events. Moreover, the risk-enhancing effect of AI is more pronounced for BHCs with weaker risk management practices. Our findings have important implications for banking performance, risk, and supervision.