Artificial Intelligence Governance and Banking Regulatory Compliance: A Multiple-Case Study of Commercial Banks in Uganda

Abstract

The rapid deployment of Artificial Intelligence (AI) in commercial banking has outpaced traditional oversight structures, creating compliance vulnerabilities within developing regulatory ecosystems. This study investigated the nexus between AI governance and banking regulatory compliance within commercial banks in Uganda. Guided by institutional theory and sociotechnical systems theory, it examined three specific objectives: evaluating algorithmic accountability structures, assessing data privacy compliance frameworks, and analyzing systemic risk mitigation protocols. The researchers adopted a qualitative multiple-case study design, purposively sampling 24 key informants, including Chief Risk Officers, Compliance Heads, and IT Directors, across four Tier-1 commercial banks in Uganda. Semi-structured interviews and institutional document analysis served as the primary data collection methods. Using an abductive thematic synthesis approach, the analysis revealed that while banks have robust technical capabilities, their AI deployment is severely constrained by fragmented internal governance, a lack of local algorithmic auditing protocols, and significant gaps in Bank of Uganda regulatory oversight. The research concludes that banking regulatory compliance in the digital era cannot be achieved through passive adherence to legacy frameworks; it requires a proactive, sociotechnical approach to algorithmic transparency. The study recommends that the Bank of Uganda issue explicit, risk-based AI governance guidelines, and that commercial banks establish independent algorithmic oversight committees to ensure operational resilience and consumer protection.