Purpose: This research investigates where formal responsibility for artificial intelligence (AI) lies within organisations and how the presence, absence, or structure of that responsibility affects their ability to govern AI effectively. Method: The study surveys 351 organisations across sectors and regions to examine AI governance roles. It focuses on authority, resources, and organisational integration, using hierarchical cluster analysis to identify governance configurations. Findings: The results indicate that formal AI governance roles are unevenly distributed and often weakly integrated into organisational structures. When these roles exist, they are usually placed below the executive level, lack sufficient authority, and differ greatly in the resources available to them. A cluster analysis reveals four governance configurations—Governance Absence, Symbolic Governance, Operational Governance, and Institutionalised Governance, indicating that governance capacity is primarily influenced by how well these roles are embedded in the structure, rather than just their presence. Implications: The findings suggest that AI governance may be better understood as a structural and organisational design issue, with potential implications for accountability and oversight. However, the relationship between governance configurations and outcomes, such as ethical risk and compliance, remains an area for future research. Originality: The study takes an absence-based approach to AI ethics, establishing a baseline for future research on governance maturity, compliance, trust, and ethical risk.
Frimpong et al. (Sun,) studied this question.