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AI Governance Institute

AI governance intelligence and practical implementation guidance for enterprise compliance, risk, legal, and security teams.

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46 reach 5 · trust 5 · quality 21 · freshness 15
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llms.txt
https://aigovernance.com/llms.txt
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6
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19
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4615 bytes
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#842238
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Categories
AI and machine learning
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Documentation: developer or product docs worth reading, nothing to call
First seen
2026-10-25T18:03:33.728Z
Last checked
2026-10-26T04:10:14.055Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-26T04:10:09.500Z. Cached copy · Source on aigovernance.com

# AI Governance Institute
> AI governance intelligence and practical implementation guidance for enterprise compliance, risk, legal, and security teams.

## Reference Library
- [Directory](https://aigovernance.com/directory): Regulations, frameworks, standards, guidelines, and enforcement actions, with source links and jurisdiction and status filters.
- [Controls](https://aigovernance.com/controls): Operational governance controls with stable IDs, maturity levels, evidence requirements, implementation guidance, and regulatory mappings.
- [Playbooks](https://aigovernance.com/playbook): Practical guides to governance decisions, implementation steps, and the artifacts teams need to produce.
- [News](https://aigovernance.com/news): Daily coverage of regulatory developments, enforcement, research, company disclosures, and model releases, with source attribution and related governance guidance.

## Starting Points
- [What is AI governance?](https://aigovernance.com/what-is-ai-governance): An introduction to AI governance and its organizational, technical, and regulatory dimensions.
- [How do we comply with the EU AI Act?](https://aigovernance.com/playbook/how-to-comply-with-eu-ai-act): Implementation guidance and links to related regulations and controls.
- [How do we govern AI agents that take autonomous actions?](https://aigovernance.com/playbook/governing-agentic-ai): Autonomy boundaries, agent identity, permissions, oversight, and audit trails.
- [How do we perform an AI risk assessment?](https://aigovernance.com/playbook/how-to-perform-ai-risk-assessment): Assessing deployment risks and selecting proportionate controls.
- [How do we ensure third-party AI vendors meet our standards?](https://aigovernance.com/playbook/third-party-ai-vendor-due-diligence): Vendor due diligence, evidence collection, and contractual safeguards.

## Implementation Resources
- [Templates and checklists](https://aigovernance.com/templates): Free implementation kits with editable templates, worked examples, and acceptance criteria. Kits can be downloaded as Markdown without an account or email.
- [Control tracker](https://aigovernance.com/controls#control-tracker): An Excel workbook for maturity scoring, owners, due dates, and regulatory coverage. The download form also subscribes readers to AI Governance Weekly, as disclosed on the page.
- [Maturity assessment](https://aigovernance.com/assessment): A self-assessment for identifying governance gaps and next steps.
- [What applies to me?](https://aigovernance.com/wizard): An interactive starting point for exploring potentially relevant regulations; not a definitive legal applicability determination.

## MCP Tools
- [AI Governance Controls MCP server](https://github.com/cody-aigov/ai-governance-mcp): Installation, tool documentation, examples, and limitations for MCP-compatible assistants. The package is named ai-governance-controls.
- The server's governance_search and governance_get tools retrieve controls and implementati
…

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