CYBRARY Why AI needs its own governance, risk, and compliance approach
Separates established GRC, AI security, and AI governance, and lands on the four decisions that need a named owner.
By the end you can
- Tell established GRC, AI security, and AI governance apart in one sentence each.
- Name what makes AI risk different from ordinary software risk.
- List the four AI decisions that must have a named owner.
Three disciplines that get mixed up
Established GRC already covers policies, controls, audits and regulatory duties for the business. It is good at systems that behave the same way every time and change only when someone ships a release.
AI security protects AI systems and the data around them from attack: prompt injection, data poisoning, model theft, leaking training data, abuse of tools an agent can call.
AI governance decides whether and how the organization uses AI at all: which uses are allowed, who is accountable for each system, how it is monitored once live, and when it is switched off.
| Discipline | The question it answers |
|---|---|
| Established GRC | Are we meeting our obligations, and can we prove it? |
| AI security | Can someone make this AI system do harm or give up what it holds? |
| AI governance | Should we use AI here, who owns it, and how do we know it still behaves? |
Why the old playbook is not enough
A model's output depends on its data and its prompts, not only on its code. The same system can drift as data changes, give different answers to the same question, and fail in ways nobody tested.
- Behavior is probabilistic, so a single passing test proves little.
- Risk lives in data lineage and in the vendor's model, both partly outside your control.
- Harms include unfair or wrong decisions about people, not only outages and breaches.
- Rules are arriving fast: the EU AI Act sorts uses by risk, and NIST AI RMF and ISO/IEC 42001 give a management structure.
The four decisions that need a named owner
Most AI incidents trace back to one of four decisions that nobody clearly owned. Each needs one named person, not a committee.
| Decision | What the owner signs off |
|---|---|
| Approve the use | This use case is allowed, at this risk level, for this purpose. |
| Accept the risk | The remaining risk after controls is known and acceptable. |
| Release to production | Testing, data checks and safeguards are done; it can go live. |
| Pause or retire | It is drifting, misbehaving or no longer needed; switch it off. |
Check yourself
A team asks whether a chatbot can be manipulated into revealing customer records. Which discipline owns that question first?
What most sets AI risk apart from ordinary software risk?
Which of these is one of the four decisions that needs a named owner?
Why one named person rather than a committee?