Agentic AI governance
Autonomous agents need more than model governance.
Agentic AI introduces tool use, memory, delegation, external actions, access to systems and changing levels of autonomy. Gamut helps organisations govern agents as operational actors with identity, ownership, boundaries and evidence.
Discuss agentic AI governanceAgent register
Record each agent’s purpose, owner, lifecycle state, autonomy level, tool permissions and risk context.
Zero-trust control
Do not assume an agent should act just because it can. Define boundaries for data, tools, code execution, transactions and escalation.
Gateway evidence
Capture decision history showing when actions were allowed, blocked, logged or escalated before execution.
Agentic governance controls to evidence
- Agent ownership and accountability
- Separated agent identities
- Tool allow-lists and permission boundaries
- Human approval gates for high-impact action
- Autonomy level and lifecycle status
- Data access limits and redaction rules
- Runtime logging and decision records
- Incident and escalation playbooks
- Threat modelling and abuse testing
- Residual risk and remediation tracking
Why this matters for EU-facing organisations
As AI systems become more autonomous, governance teams need to evidence not only what the system is, but what it can do, who approved it, what data it can touch and how risky actions are controlled. That is where Gamut’s Agentic CISO, GTSAF and Gateway model become valuable.