Before Adding Another AI Tool, Ask Who Owns the Decision
AI governance begins with decision rights. Before expanding the toolset, leadership should know who approves use, owns outcomes, sets boundaries, accepts risk, and decides when to stop.
The easiest part of AI governance may be writing the policy.
The harder part is deciding who has authority to act when the policy meets a real business decision.
A team wants to use an AI assistant with customer information. A department wants to buy a new AI platform. A workflow starts relying on AI-generated recommendations. A pilot is ready for production. An AI system can now take an action, not just suggest one.
Who decides?
That question should come before the next tool.
AI decisions cross the organization
AI governance is often framed as a technology or compliance job. The decisions don't stay there.
Technology evaluates the platform. Security reviews access and data handling. Legal and privacy advise on obligations. Procurement manages the vendor. A business leader owns the process. Finance approves the investment. Employees still need practical guidance on what's allowed.
Involving all of those stakeholders doesn't create accountability. Someone still has to own the decision.
NIST's Generative AI Profile is useful context. It addresses generative AI risk across design, development, use, and evaluation.[1] That is a lifecycle, not a one-time technical control.
So the executive question isn't only “Do we have an AI policy?” It is:
Do we know who can decide what, under which conditions, and with what evidence?
Five ownership questions to settle early
Before approving another AI tool or scaling an existing one, leadership should be able to answer five questions.
Evidence
Sources
External references support specific factual claims in this article. They do not imply that Mickom conforms to, is certified by, or is endorsed by any referenced organization.
- [1] National Institute of Standards and Technology (opens in a new tab)
- [2] Deloitte (opens in a new tab)