What are key components of a defined AI governance system?

• A. Mature I&T governance processes, appropriate governance structures, and skilled resources
• B. Ad hoc governance with little oversight
• C. Only regulatory compliance
• D. Isolated data silos with no governance

Answer: (A)

A defined AI governance system is built on structured oversight that brings together how AI is governed, who is responsible, and the people with the expertise to enforce it. The best approach combines mature governance processes for AI life cycle activities (development, deployment, monitoring, change control, and risk management), formal governance structures that assign roles, accountability, and escalation paths, and skilled resources capable of applying policies, evaluating risks, and enforcing controls. When these elements exist together, the organization can consistently manage risks, ensure accountability, and align AI use with business goals and ethics.

Ad hoc governance with little oversight, on the other hand, leads to inconsistent decisions and unaddressed risks. Focusing only on regulatory compliance misses broader risk management, ethical considerations, and ongoing control. Isolated data silos with no governance undermine data quality, transparency, and the ability to monitor and control AI systems.