What is COBIT's application to the AI life cycle?

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Multiple Choice

What is COBIT's application to the AI life cycle?

Explanation:
The idea being tested is how to govern AI across its life cycle using a broad, enterprise-wide framework. COBIT is about governance and management of IT assets and processes, so when you apply it to AI you’re looking at how to align AI initiatives with business objectives, manage risk, ensure value delivery, and provide oversight across the entire lifecycle—from planning and acquisition to deployment, operation, and eventual retirement. It’s not about writing code or building models; it’s about setting policy, controls, and performance measures that steer AI projects in a way that supports the business and protects the organization. That holistic focus is why this answer is the best. COBIT guides governance, establishes accountability, and supports decision-making across technology-enabled initiatives, ensuring AI activities stay aligned with strategy and risk tolerance. The other options miss the mark because they either place emphasis on something outside governance (defining exact AI code), narrow it to a single domain (cybersecurity only), or mix it with project scheduling, which is more project management than governance.

The idea being tested is how to govern AI across its life cycle using a broad, enterprise-wide framework. COBIT is about governance and management of IT assets and processes, so when you apply it to AI you’re looking at how to align AI initiatives with business objectives, manage risk, ensure value delivery, and provide oversight across the entire lifecycle—from planning and acquisition to deployment, operation, and eventual retirement. It’s not about writing code or building models; it’s about setting policy, controls, and performance measures that steer AI projects in a way that supports the business and protects the organization.

That holistic focus is why this answer is the best. COBIT guides governance, establishes accountability, and supports decision-making across technology-enabled initiatives, ensuring AI activities stay aligned with strategy and risk tolerance. The other options miss the mark because they either place emphasis on something outside governance (defining exact AI code), narrow it to a single domain (cybersecurity only), or mix it with project scheduling, which is more project management than governance.

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