312-41 practice question 27 of 35

An organization has moved beyond early AI pilots and is now supporting AI use across several business teams. Initially, every AI request required…

Choose your answer, then check it against the explanation.

An organization has moved beyond early AI pilots and is now supporting AI use across several business teams. Initially, every AI request required centralized approval and extensive manual oversight, which limited scale. As adoption increased, the organization introduced differentiated approval paths based on use-case risk, allowed teams to independently use a predefined set of commonly accepted AI tools, and reduced manual review for lower-risk applications while retaining additional oversight for more sensitive use cases. Although governance is still actively involved, controls are no longer applied uniformly to every request. Based on the governance characteristics, which stage of AI governance maturity best reflects the organization’s current approach?

Answer options

Correct Answer:

Explanation

The organization's approach has evolved from highly restrictive, centralized oversight to a more nuanced system. By implementing "differentiated approval paths based on use-case risk" and allowing independent use of predefined tools, they are balancing the need for control with the goal of enabling broader adoption. This risk-based, flexible approach is a hallmark of the "Growth Stage," where governance matures to support scaling AI responsibly without stifling innovation.

Why Incorrect

A. Early Stage – Restrictive Controls: This describes the organization's past state, not its current, more flexible approach.

C. Mature Stage – Enabling Guardrails: This stage implies more automation and federated autonomy within established guardrails, a step beyond the current "balanced" approach.

D. Early Stage – Manual Review Processes: The organization is actively moving away from universal manual review, making this description outdated.

References

1. National Institute of Standards and Technology (NIST). (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). (NIST AI 100-1). The framework's "Govern" function emphasizes establishing risk-based governance that adapts to context, moving beyond one-size-fits-all controls (Section 4.1, p. 20).

2. Stanford Institute for Human-Centered Artificial Intelligence (HAI). (2021). Building a National AI Research Resource: A Blueprint for the National AI Research Cloud. This report discusses governance models for AI resources, highlighting the need for tiered access and risk-based controls to balance safety with broad access as a platform matures (Chapter 4, "Governance").

Question 27 of 35

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