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2 changes: 1 addition & 1 deletion docs/ai-coder/ai-governance.md
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Organizations adopting AI coding tools at scale often encounter operational and
security challenges that traditional developer tooling doesn't address.

### Auditing AI activity across teams

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Without centralized monitoring, teams have no way to understand how AI tools are
being used across the organization. AI Gateway provides audit trails of prompts,
token usage, and tool invocations, giving administrators insight into AI
adoption patterns and potential issues.

### Restricting agent network access

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AI agents can make arbitrary network requests, potentially accessing unauthorized services or exfiltrating data.
Agent Firewall enforces process-level policies that restrict which domains agents can reach and what actions they can perform,
preventing unintended data exposure and destructive operations like `rm -rf`.
preventing unintended data exposure.

### Centralizing API key management

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Managing individual API keys for AI providers across hundreds of developers
creates security risks and administrative overhead. AI Gateway centralizes
authentication so users authenticate through Coder, eliminating the need to
distribute and rotate provider API keys.

### Standardizing MCP tools and servers

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Different teams may use different MCP servers and tools with varying security
postures. AI Gateway enables centralized MCP administration, allowing
organizations to define approved tools and servers that all users can access.

### Measuring AI adoption and spend

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Without usage data, it's hard to justify AI tooling investments or identify
high-leverage use cases. AI Gateway captures metrics on token spend, adoption
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will receive a warning to [contact their account team](https://coder.com/contact)
to remediate.

### Tracking Agent Workspace Builds

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Admins can monitor Agent Workspace Build usage from the Coder dashboard.
Navigate to **Deployment** > **Licenses** to view current usage against your
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