The EU AI Act enforcement deadlines are here. NIST AI RMF 2.0 just dropped. And most enterprise security teams are still running AI governance on spreadsheets.

Here are the 5 gaps I see over and over when auditing AI deployments:

1. No Model Inventory

You can't govern what you can't see. Most orgs have 3-5x more AI models in production than their security team knows about. Shadow AI is the new shadow IT.

2. Data Lineage Blindspots

If you can't trace which data trained which model and where inference outputs flow, you're one regulatory inquiry away from a very bad day.

3. No Continuous Monitoring

Point-in-time assessments are not governance. Models drift. Data distributions shift. If your governance cadence is quarterly, your risk exposure is real-time.

4. Missing AI Incident Response

Your SOC has playbooks for network intrusions. Do you have one for model poisoning? For adversarial prompt injection at scale?

5. Compliance Theater

Checking a box without implementing controls creates false confidence. Real governance means automated policy enforcement, not PDF checklists.

We built GovLayer AI to close every one of these gaps — real-time monitoring, automated compliance mapping, full data-layer security, and incident response orchestration for AI systems.

If any of these sound familiar, your AI stack needs a governance layer.