Is an AI policy the same as AI governance?

An AI policy gives staff practical rules for everyday AI use. AI governance is broader and covers ownership, risk management, approved tools, assurance, training and oversight.

Which should an organisation create first?

Many organisations start with an AI policy because it gives staff immediate guidance. Governance can then grow around the policy through ownership, review, approved tools and risk processes.

Can a small organisation have AI governance?

Yes. AI governance does not have to be complicated. A small organisation can define who owns AI decisions, which tools are approved, what information is protected and how concerns are reviewed.

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AI policy vs AI governance

An AI policy gives people clear rules for using AI at work. AI governance is the wider set of decisions, roles and controls that help those rules stay useful as AI use grows.

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The simple difference

An AI policy is a practical document. It tells staff which AI tools they may use, what information must stay protected, when human review is required and who to ask when something is unclear.

AI governance is the operating model behind those rules. It covers ownership, approved tools, risk decisions, training, review, monitoring, exceptions and how the organisation keeps AI use aligned with its responsibilities.

What an AI policy does

A good AI usage policy turns a broad topic into everyday guidance. It should help people make sensible decisions without needing to become specialists in data protection, information security or AI regulation.

Sets rules for public tools such as ChatGPT, Gemini and Claude
Explains how Microsoft Copilot or other approved tools may be used
Protects personal, confidential and commercially sensitive information
Requires human review before important AI-assisted work is used
Defines responsibilities for staff, managers and tool owners
Gives people a route for questions, exceptions and concerns

What AI governance covers

Governance is the continuing management of AI use. It helps the organisation decide which tools are acceptable, which uses need approval, what risks need review and how staff should be supported.

Ownership

Who is responsible for AI policy, approved tools, exceptions, incidents and review?

Risk decisions

Which AI uses are low risk, which need checks and which are not appropriate?

Training

What do staff and managers need to know before AI becomes part of daily work?

Assurance

How will the organisation check that AI use remains safe, accurate and useful?

How they fit together

The policy is often the first useful output because it gives staff something clear to follow. Governance then keeps that policy alive by reviewing tools, learning from incidents, updating training and making decisions about new use cases.

For example, a policy may say staff must only use approved AI tools for customer information. Governance decides which tools are approved, how that decision is made, who reviews new tools and what evidence is needed before a tool is added to the list.

Practical example

Policy question

Can staff paste customer emails into an AI tool to draft a reply?

Governance question

Which tool, data protection checks, access controls and review steps make that use acceptable?

Policy answer

Only use approved tools and do not enter personal or confidential data into public AI systems.

Governance answer

Maintain an approved tools list, define permitted data types and review higher-risk use cases.

When you need more than a policy

A policy may be enough as a starting point, especially for smaller teams. You probably need broader governance when AI is being used with sensitive data, client work, regulated activity, high-impact decisions or integrated business systems.

Staff are already using several AI tools informally
Microsoft Copilot, Gemini or another integrated tool is being rolled out
AI is being used with personal, client, pupil, patient or employee data
AI-assisted outputs affect customers, beneficiaries or public content
The organisation has ISO 27001, ISO 42001, GDPR or security obligations to consider

AI governance checklist

Define a named owner for AI governance and policy review
Create and maintain an approved AI tools list
Set rules for personal, confidential and sensitive information
Train staff on safe, responsible and useful AI use
Review higher-risk use cases before they are adopted
Keep a route for questions, incidents and exceptions
Review the policy when tools, risks or working practices change

FAQ

Common questions about AI policy and governance

Is an AI policy enough?

It can be enough as a first step. As AI use grows, the organisation should also define ownership, approved tools, training, risk review and monitoring.

Does AI governance need to be formal?

Not always. Small organisations can keep governance simple: a named owner, approved tools list, practical policy, review dates and clear routes for questions.

Where should we start?

Start by creating a practical AI policy, then use it to identify decisions about approved tools, personal data, staff training and higher-risk AI use.