Which aspects are typically overseen by AI governance?

• A. It only manages license compliance and software updates.
• B. It focuses on hardware reliability and network uptime.
• C. It ensures marketing strategies are compliant with ads policy.
• D. It oversees ethical use, bias, accountability, data privacy, model risk, and alignment with business goals.

Answer: (D)

AI governance is about establishing the policies, processes, and controls that guide how AI models are developed, deployed, monitored, and retired. It focuses on ensuring responsible and accountable use of AI across the organization, covering ethical considerations, detection and mitigation of bias, accountability for decisions, protecting data privacy, managing model risk (including performance, robustness, and adversarial risk), and ensuring alignment with business goals and regulatory requirements. This broad oversight helps balance innovation with safety and trust. Other areas like license compliance and software updates belong to software asset management; hardware reliability and network uptime belong to IT operations; and marketing policy compliance relates to marketing governance. While those areas can intersect with AI work, true AI governance encompasses the end-to-end lifecycle and the governance framework itself.