12 AI Policy Templates And Frameworks Every IT Leader Should Review In 2026

Most organizations have AI tools. Far fewer have policies that address AI agents, security and governance. These templates can help close the gap.

Editor's note: This article was originally published in July 2025 and has been updated to reflect emerging governance challenges around AI agents, autonomous systems and AI security.

Artificial intelligence has moved beyond experimentation and into production environments, creating new governance, security and operational challenges for IT leaders.

While organizations continue to grapple with copyright, privacy, transparency and AI hallucinations, many are now evaluating or deploying autonomous AI agents capable of accessing data, interacting with applications and taking actions on behalf of users.

Now agentic AI is to 2025 what generative AI was to 2023. IT leaders seem keen on deploying AI agents within their operations. According to the 2025 Connectivity Benchmark Report by MuleSoft and Deloitte Digital, 93 percent of IT leaders report intentions to introduce autonomous AI agents within the next two years, and nearly half have already done so.

Agentic AI can introduce more security and management issues for IT. For example, an agent could make “an uncontrolled or unexpected decision that might lead to a security failure. Example, that could be an AI agent is carrying out automated incident response tasks and it incorrectly shuts down a critical production server, and it causes downtime, so the AI thought something wrong was happening, but it made an unexpected decision, and maybe it shut down something that was super critical,” Ian Swanson, the CEO of Protect AI, told MES Computing in an interview.

Moreover, agents typically need to log in and authenticate to existing systems. This means they need identity and access management just as with human user accounts. Securing and managing agent logins is something that Strata Identity attempts to address with its recent announcement of its new product, Identity Orchestration for AI Agents.

With AI agents poised to access enterprise applications, handle sensitive business data and automate decisions, organizations need AI policies that go beyond acceptable-use guidelines. Effective AI governance now requires more stringent controls around risk management, oversight, identity and access management, and accountability.

The Information Systems Audit and Control Association (ISACA) offers several considerations to take when crafting AI corporate policy:

Assess your organization’s AI needs: How will AI be used? By which departments? Which tools will be needed to supplement business operations?
Understand regulations: According to ISACA, “Research the legal and regulatory requirements related to generative AI in your industry and jurisdiction.”
Perform a risk assessment: These include assessing any potential technical or ethical risks (like any generated misinformation).
Engage stakeholders: Any individual or team within the organization who may use or be impacted by the use of AI should be involved in creating policy.
Make plans to share the policy not only internally, but externally: Partners and customers should be fully aware of your organization’s AI policy.

To get a jump start on creating a policy, there are several templates available. It’s important to note these templates aren’t just for filling out and then declaring to management or your board, “here is our policy.” Instead, they should be used as a framework to customize a policy that is a right fit for your organization’s needs.

What A Modern AI Policy Must Include

Midmarket leaders are discovering that AI governance requires more than acceptable use rules and must address data, risk and operational oversight.

AI Agent Governance

Which agents are approved?

What systems can they access?

Who owns them?

AI Identity And Authentication

Agents need identities and credentials.

Least privilege should still apply.

Human Oversight Requirements

Which decisions require approval?

Which can be automated?

Data Governance

What data can be entered?

What data is prohibited?

Monitoring And Auditing

Logging AI decisions

Tracking actions

Incident response procedures

AI Governance Frameworks And Standards

NIST AI Risk Management Framework (AI RMF)

The National Institute of Standards and Technology's AI Risk Management Framework is not a fill-in-the-blanks policy template, but it provides a widely adopted framework for governing AI risk. The guidance helps organizations establish processes for AI governance, risk assessment, measurement and ongoing management. For IT leaders building or revising AI policies, the framework can serve as a foundation for defining controls, accountability and oversight.

Microsoft Responsible AI Standard

Microsoft offers a very detailed guideline for responsibly implementing AI policies and standards.

AI Policy Templates For Organizations

Responsible Artificial Intelligence’s AI Policy Template

RAI’s downloadable AI policy template complies with ISO/IEC 42001 and NIST standards. The template offers guidance on creating governance rules, ethical practices, risk management, project management, as well as procurement and documentation tools.

SANS Institute Artificial Intelligence Policy

The SANS Institute, in its over-30-year history, has been a leading source for cybersecurity certification, training and research. SANS offers an AI template which can be downloaded from its site.

TrustCloud’s Trust Community Artificial Intelligence Usage Policy Template

TrustCloud, which offers a trust assurance platform to help organizations streamline and meet regulatory compliances, achieve data security and transparency and fulfill other requirements that promote trust, offers an AI policy template through its Trust Community site. The template “outlines guidelines and procedures for the responsible and ethical use of artificial intelligence (AI) technologies within an organization.”

Workable’s AI Tool Usage Policy

Workable offers a template that can help businesses get started on creating a policy around the use of AI tools.

AI Governance Library’s AI Policy Template

This customizable template offers guidance on setting definitions on AI and AI systems within an organization, how to document specific AI goals, creating governance, adhering to regulatory compliance, and more.

Institute of AI Studies’ AI Policy Template

Targeted more for gen AI, the AI Institute's template helps organizations craft AI guidelines related to privacy, transparency, risks, and auditing.

Jasper.ai’s AI Policy Template for Businesses

Jasper.ai, which creates AI-based marketing solutions, offers its template for businesses, with instruction on promoting ethical AI usage, minimizing risk, educating teams on AI use, and more.

Industry-Specific AI Policy Templates

NFPS.AI’s AI Policy Template

NFPS.AI is a platform that helps nonprofits and not-for-profit organizations “harness AI technology to drive innovation.” The template is targeted to nonprofits and not-for-profits.

Society for Human Resource Management’s Generative AI Usage Policy Template

SHRM is one of the leading organizations for HR professionals. It offers a Gen AI policy template; however, it’s only accessible to SHRM members.

Additional AI Governance Resources

Okta AI Identity Security Compliance Checklist

As AI agents increasingly require access to enterprise applications and data, identity governance has become a key component of AI policy. Okta's checklist focuses on access controls, authentication, compliance and governance considerations that organizations should address before granting AI systems access to corporate resources.

5 Rules To Getting Started With AI Governance

AI Data Governance: What Midmarket IT Leaders Must Prove In 2026

Agentic AI Security And Risk Assessment Are Poised To Become A Major Focus For IT Leaders

Copilot 'AI Worm' Raises Flag About Governance, AI Productivity Tools