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Generative AI Policies: Aligning Organizational Governance with the NIST AI Risk Management Framework


Generative AI is moving faster than most organizational control structures. Employees are already using tools like ChatGPT, Copilot, Claude, and image generators to write code, summarize documents, build presentations, and analyze data—often without security or legal review.

Banning generative AI outright is rarely effective. Ignoring it is worse.

What organizations need is a clear, enforceable Generative AI policy that:

  • Enables productivity
  • Protects sensitive data
  • Manages legal, ethical, and security risk
  • Aligns with a recognized framework

The NIST AI Risk Management Framework (AI RMF) provides a strong foundation for doing exactly that.

Why Generative AI Policies Matter

Generative AI introduces new risk categories that traditional IT or acceptable-use policies do not fully address:

  • Data leakage through prompts and outputs
  • Model hallucinations treated as fact
  • Intellectual property exposure
  • Bias and ethical risk
  • Shadow AI adoption
  • Regulatory and compliance gaps

A well-designed policy is not about restricting innovation—it is about setting guardrails so innovation happens safely.

Using the NIST AI Risk Management Framework as the Backbone

The NIST AI RMF organizes AI governance around four core functions:

  1. Govern
  1. Map
  1. Measure
  1. Manage

An effective Generative AI policy should explicitly support each of these.

1. Govern: Establish Ownership, Accountability, and Direction

Policy alignment starts with governance.


Your Generative AI policy should clearly define:

  • Who owns AI risk (Security, Legal, Privacy, Compliance, AI Governance Committee)
  • Who approves new AI tools or use cases
  • How policy compliance is monitored and enforced
  • Executive sponsorship
  • Defined roles and responsibilities
  • Clear acceptable and prohibited use
  • Alignment with existing security, privacy, and data policies

Key policy concepts aligned to NIST Govern:

Without governance, AI adoption becomes decentralized and unmanageable.

2. Map: Define How and Where Generative AI Is Used

Before you can manage risk, you must understand context.

Your policy should require teams to:

  • Identify approved AI tools and platforms
  • Declare business use cases
  • Classify data involved (public, internal, confidential, regulated)
  • Document high-risk use cases (e.g., code generation, legal drafting, customer interaction)

This directly supports NIST’s Map function, which focuses on understanding AI systems, stakeholders, and environments of use.

3. Measure: Assess Risk and Impact

Generative AI risk is not theoretical—it is measurable.


A strong policy links AI usage to:

  • Data classification standards
  • Risk assessments for sensitive use cases
  • Periodic reviews of AI outputs for accuracy, bias, and misuse
  • Monitoring for policy violations or data exposure

This aligns with the Measure function of the NIST framework, which emphasizes evaluation, testing, and ongoing risk assessment.

4. Manage: Control, Respond, and Improve

Finally, policies must support real-world operations.

Your Generative AI policy should define:

  • How violations are handled
  • When AI use must be paused or revoked
  • Incident response procedures related to AI misuse
  • Continuous improvement and policy updates as tools evolve

This ensures your organization can adapt as generative AI capabilities and risks change.

Common Policy Pitfalls to Avoid

  • Writing a policy that is too technical for employees to understand
  • Treating generative AI like traditional software
  • Failing to address prompt data as a form of data sharing
  • Not involving Legal, HR, and Privacy
  • Publishing a policy without training or awareness

A policy only works if people can and will follow it.

Sample Generative AI Policy (Template)

Below is a baseline Generative AI policy aligned with the NIST AI Risk Management Framework. This is not legal advice but is suitable as a starting point for most organizations.

Generative Artificial Intelligence (AI) Policy

1. Purpose

The purpose of this policy is to establish guidelines for the responsible, secure, and compliant use of Generative Artificial Intelligence (AI) technologies within the organization, while aligning with the NIST AI Risk Management Framework.

2. Scope

This policy applies to:

  • All employees, contractors, and third parties
  • All generative AI tools, platforms, and services used for business purposes
  • All data processed, input, or generated by AI systems on behalf of the organization

3. Definitions

Generative AI: AI systems capable of producing text, code, images, audio, or other content in response to prompts or inputs.

AI Tool: Any internally developed or third-party AI system used to generate content or assist decision-making.

4. Governance and Oversight (NIST: Govern)

  • The organization will maintain oversight of Generative AI usage through designated owners (e.g., Information Security, Legal, Privacy).
  • Only approved AI tools may be used for business purposes.
  • High-risk AI use cases require documented review and approval prior to implementation.

5. Acceptable Use

Employees may use approved Generative AI tools to:

  • Draft non-confidential content
  • Assist with coding and development using non-sensitive data
  • Summarize publicly available or approved internal information
  • Improve productivity in ways consistent with job responsibilities

6. Prohibited Use

The following are strictly prohibited:

  • Entering confidential, regulated, or personal data into unapproved AI tools
  • Using AI to generate legal, medical, or financial advice without authorization
  • Representing AI-generated content as human-reviewed when it is not
  • Circumventing security controls using AI-generated code or instructions

7. Data Protection and Privacy (NIST: Map / Measure)

  • Data shared with AI tools must comply with the organization’s data classification and privacy policies.
  • Prompts and outputs are considered data and may be logged, monitored, or reviewed.
  • Employees must assume AI tool providers may retain submitted data unless otherwise contractually restricted.

8. Risk Assessment and Monitoring (NIST: Measure)

  • AI use cases involving sensitive data or decision-making must undergo risk assessment.
  • AI outputs should be reviewed for accuracy, bias, and appropriateness before use.
  • The organization may periodically audit AI usage for compliance with this policy.

9. Incident Response and Enforcement (NIST: Manage)

  • Suspected AI misuse or data exposure must be reported immediately.
  • Violations of this policy may result in disciplinary action.
  • AI-related incidents will be handled under the organization’s incident response process.

10. Training and Awareness

  • Employees will receive training on responsible Generative AI use.
  • Policy updates will be communicated as tools and risks evolve.

11. Policy Review

This policy will be reviewed at least annually or upon significant changes in AI technology, regulation, or organizational risk posture.

Final Thoughts

Generative AI is not a future problem—it is a current governance challenge.

Organizations that align their AI policies with the NIST AI Risk Management Framework gain:

  • Structure without stifling innovation
  • Defensible decision-making
  • Clear accountability
  • Reduced security and compliance risk

A Generative AI policy is no longer optional. It is a foundational control for modern security programs.

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