AI Agent Governance Framework
A comprehensive governance framework for managing AI agents at scale in your UAE organization.
Step-by-step guide
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Establish ownership
Assign a governance owner for AI agents - typically IT, operations, or a dedicated AI team. Define their responsibilities.
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Create an agent inventory
Document every deployed agent: what it does, which tools it accesses, who owns it, when it was last reviewed.
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Define access policies
Standardize how agent permissions are granted, reviewed, and revoked. Apply least-privilege consistently.
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Set up change management
Require approval for agent configuration changes. Log all changes with who, what, when, and why.
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Establish review cycles
Quarterly reviews of each agent: performance, access scope, alignment with business needs, security posture.
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Plan for decommissioning
Define how agents are retired: data retention, access revocation, knowledge transfer, and stakeholder notification.
Key takeaways
- Governance becomes critical at 3+ agents - establish it before you scale
- An agent inventory is the foundation of governance - you can't govern what you don't track
- Change management prevents configuration drift and unauthorized modifications
- Regular reviews catch permission creep and misaligned workflows before they cause issues
Ownership Model
Clear assignment of who owns, manages, and is accountable for each AI agent in your organization.
Agent Inventory System
A standardized registry of all deployed agents - capabilities, access, ownership, and review dates.
Access Policy Framework
Consistent policies for granting, reviewing, and revoking agent permissions across your organization.
Change Management Process
Approval workflows for agent changes with full audit trails - who changed what, when, and why.
Review Cycle Template
Structured quarterly reviews covering performance, security, compliance, and business alignment.
Decommissioning Protocol
How to safely retire agents - data handling, access cleanup, and stakeholder communication.
FAQ
When should we implement governance?
Before your third agent deployment. One or two agents can be managed informally. At three+, you need structure.
Who should own AI governance?
Typically IT or operations leadership. In larger organizations, a dedicated AI/automation team. The key is clear accountability.
Is this relevant for small businesses?
Basic governance (inventory, access review, change logging) is valuable at any size. The full framework scales with your agent portfolio.
Govern your AI agents
Set up proper AI governance.