Free AI Governance Framework Builder
Build an AI governance framework your organization can adopt, worded to align with the NIST AI Risk Management Framework 1.0 and the management-system requirements of ISO/IEC 42001. Answer a short guided form, describe the AI systems in scope, then build the framework and download it as Word or PDF. It is free and needs no sign-up. Your details are processed securely to write the framework and are never stored, sold, or used for training.
An AI governance framework is the operating model an organization uses to govern, map, measure, and manage its AI: who owns each system, how risk is assessed, what controls apply, and how it is all reviewed. This free tool assembles that framework from a guided form, worded to align with the NIST AI RMF 1.0 and ISO/IEC 42001, and lets you download it as Word or PDF, with no paywall and no sign-up.
Framework details
Fill in your organization details and describe the AI in scope. You get a complete AI governance framework worded to align with the NIST AI RMF 1.0 and ISO/IEC 42001, ready to download as Word or PDF.
Organization
Your framework will appear here. Fill in the details on the left and select Generate framework.
How the AI governance framework builder works
Describe your organization
Enter your organization, choose your industry, and describe the AI systems in scope and where you want your governance to get to.
Build your framework
The tool writes a framework from your details, worded to align with the NIST AI RMF 1.0 and ISO/IEC 42001, covering how you govern, map, measure, and manage AI risk. Results come back in seconds.
Download and review
Export the framework as a PDF or an editable Word file, then have it reviewed by legal or compliance counsel before you adopt it.
Free, private, and built on NIST AI RMF 1.0 and ISO/IEC 42001
Most framework generators sit behind a lead form or keep a copy of what you enter. This one asks for no sign-up and keeps nothing. Building a framework needs a language model, so your details are sent to our server and processed there, then discarded. The sections are worded to line up with the four functions of the NIST AI Risk Management Framework 1.0 and the management-system requirements of ISO/IEC 42001.
We built this from our own AI governance programme, not from a summary of the standard: see BlockSurvey's AI Policy for how we apply the same functions to ourselves.
Processed, never kept
Your details are processed securely to write the framework and are never stored, sold, or used for training. Keep the form to organization-level details and leave secrets, personal data, and PHI out.
No account required
No sign-up and no email wall. A fair-use rate limit is the only thing standing between you and the tool.
Free, real download
The complete framework as an editable Word file or PDF at no cost, not a watermarked sample.
What the framework includes
A structured framework generated from your details, worded to align with the four NIST AI RMF 1.0 functions and ISO/IEC 42001:
- Purpose and scope, covering the AI systems your organization builds, buys, and uses.
- Govern: roles, responsibilities, and a designated AI governance owner.
- Map: how AI systems and their context and risks are identified and recorded.
- Measure: how risk, performance, and impact are assessed and tracked.
- Manage: the controls, mitigations, and monitoring applied to each system.
- An AI system inventory or register that ties owners to systems.
- Risk assessment and impact-assessment triggers for higher-risk use.
- Data governance, privacy, and lawful basis consistent with the GDPR.
- Human oversight of consequential AI-assisted decisions.
- Incident response, enforcement, and an at-least-annual review cadence.
- A counsel-review legal notice added to the end of the document.
NIST AI RMF 1.0 vs ISO/IEC 42001
A good AI governance framework draws on both: the NIST AI RMF 1.0 tells you how to reason about AI risk and govern it, while ISO/IEC 42001 tells you how to run a management system that proves you did. The sections in this builder are worded to feed either one.
| NIST AI RMF 1.0 | ISO/IEC 42001 | |
|---|---|---|
| What it is | A voluntary risk management framework published by NIST. | A certifiable management system standard for AI, published by ISO and IEC. |
| Structure | Four core functions: govern, map, measure, manage. | Plan-do-check-act clauses plus Annex A controls. |
| Role in a framework | Supplies the functions this framework is structured around. | Supplies the management-system discipline: ownership, review, and evidence. |
| Can you certify? | No. You self-adopt and document your reasoning. | Yes. An accredited body audits and certifies your management system. |
| Relation to law | Referenced widely in US policy; not itself binding. | Maps to EU AI Act obligations and supports GDPR Article 35 impact assessments. |
Built for every team working with AI
Whether you ship models or just bought your first AI tool, a written governance framework is what lets you explain your AI to a customer, an auditor, or a regulator. This builder gives you a structured starting point, and it pairs well with an AI survey platform when the data you feed those systems comes from people.
Compliance & privacy teams
Stand up an AI governance framework without starting from a blank page.
Legal & risk
Get a framework-aligned draft to review and tailor, not a generic template.
Product & engineering
Give teams shipping AI a clear operating model to build against.
Researchers & data teams
Set out how you handle data provenance, privacy, and human oversight.
Startups adopting AI
Answer enterprise AI questionnaires with a framework you can actually point to.
Vendors selling into enterprise
Show buyers the framework that governs the AI in your product.
Your framework just committed to data governance.
The data-governance and privacy sections you built only hold if the tools you collect data with honour them too. BlockSurvey is an AI survey platform, encrypted end to end, with a published AI policy you can cite in your own vendor assessment, so responses are never sold, mined, or used to train models.
