AI governance’s real gap is accountability, not technology

AI governance failures are increasingly about unclear ownership and broken workflows, not a lack of tooling: enterprises may have dashboards and policies, but they still struggle to assign accountability for approvals, monitoring, and outcomes. For CIOs, the strategic implication is that AI scale will depend on redesigning jobs and embedding governance into operating processes, especially as agentic systems make errors compound across multi-step workflows and raise compliance, legal, and reputational risk.