3 real examples of AI policies
This chapter presents three real AI policy examples from different types of organizations. Each example shows how organizations make their AI policy.
By looking at real policies, it becomes easier to see how an AI policy works in practice and which elements can be useful for your own organization.
Example 1: Watford Borough Council
This AI policy was developed for a local government organization that provides public services to residents and businesses. The policy is aimed at employees, contractors, and consultants who use AI tools in their daily work.
One strong aspect of this policy is the clear focus on practical use in daily work. The document explains how employees may use AI tools and provides concrete examples of what is allowed and what is not.
For example, it clearly explains that personal data may not be entered into public AI tools and illustrates this with realistic workplace scenarios.
Finally, the policy treats AI as a developing technology and clearly states that the document will be reviewed regularly. By describing the policy as something that evolves over time, the organization acknowledges that AI will continue to change.
Example 2: Firstsource
This AI policy example comes from a large services organization that works with clients and customer data at scale. The document is written for employees, contractors, and third parties who use generative AI on company devices or networks.
The policy is strong in the way it uses guardrails to turn principles into action. Instead of only stating high level values, it includes practical guidelines that employees can apply immediately. The idea of treating anything entered into a generative AI tool as if it could become public is a simple rule that employees understand quickly.
Another practical and interesting part is the way the policy connects to compliance and contracts. It highlights that AI is not only a user behavior topic but also a procurement and supplier topic.
Example 3: NARPM Association
This AI policy comes from a professional membership association that produces content, guidance, and resources for a broad community of members and partners. It is written for a wide group, including members, contributors, contractors, and anyone who handles NARPM content or data.
One strong aspect is how clearly the policy defines who it applies to and why it exists. By naming all stakeholders, it addresses a common blind spot. Many organizations focus only on employees, while contractors and contributors often create content and handle data as well.
The confidentiality section is especially strong because it translates generative AI risks into concrete examples. It names specific categories of information that should never be shared, such as personally identifiable information, credentials, and proprietary materials. This creates extra awareness among employees.
Lastly, the it handles intellectual property risk in a way that fits the organization’s daily work. Instead of only describing the legal risks in general terms, the policy translates them into rules that match the type of content the organization produces.
What should be included in an AI policy?
An AI policy can be structured in different ways depending on the size of the organization and the way AI is used in daily work. There is no single correct format that fits every organization.
What matters most is that the policy provides clear guidance and is practical to apply. A well structured policy helps employees understand what is expected of them when using AI.
Learn how to create an effective AI policy for your company by using our practical guidance.
- Easy to understand.
- Step by step approach.
- No technical knowledge required.
The structure below provides a practical example of what can be included in an AI policy. It focuses on the most important topics that most organizations need to address when introducing AI.
- Purpose and scope
- AI strategy and vision
- Pratical rules for using AI
- Privacy and security
- Training and maintenance
1. Purpose and scope
The first chapter explains why the AI policy exists and who it applies to. It describes the goals of the policy and what the organization wants to achieve with responsible AI use. It also clarifies which employees and external parties must follow the policy.
Clear definitions help prevent confusion. It should be explained what is considered AI within the policy and which applications fall within scope. AI includes more than chatbots and text generators. Many software tools contain AI functionality, which makes a clear boundary important.
It is also useful to indicate where employees can go with questions and requests for new AI tools. A clear point of contact helps employees use AI with confidence.
2. AI strategy and vision
The second chapter describes how the organization wants to use AI and where it creates value. A clear vision helps employees understand why AI is used and how it supports the organization.
It also explains how people and AI work together. Employees remain responsible for their work and should critically review AI output. AI supports the work process but does not replace human judgment.
Linking the policy to existing laws and regulations provides additional direction. Regulations related to privacy, security, and AI use may influence how AI is applied within the organization.
3. Pratical rules for using AI
This chapter defines the practical rules for using AI in daily work. It explains which AI tools are allowed and how approval for new tools works.
It can describe examples of appropriate use, such as brainstorming, drafting texts, or summarizing information. Concrete examples help employees understand how AI can support their work.
It is equally important to describe situations where AI should not be used. Extra caution is needed when working with confidential information or when careful human judgment is required.
4. Privacy and security
Privacy and security are essential conditions for using AI responsibly. Therefore a special chapter should specifically explain how employees must handle company data and personal information when using AI tools.
Sensitive or personal data should only be used when proper safeguards are in place. Clear rules help prevent data breaches and loss of control over information.
Security measures such as approved tools and controlled access help protect organizational data. Clear agreements about data storage and access rights reduce risks.
5. Training and maintenance
An AI policy only works when employees understand how to apply it. Training is an essential component for giving the AI policy practical value. It can also serve as an effective way to improve AI data literacy among employees.
Training can help employees develop practical skills and awareness of risks. Clear communication ensures employees know where to find the policy and what is expected of them.
Because AI develops quickly, the policy should be reviewed regularly. Updates help keep the policy aligned with new tools and new developments.
What makes a good AI policy example?
This chapter explains what makes a good AI policy example. It describes the elements that help turn an AI policy into a practical and usable document for the organization.
It provides guidance on how to make a policy understandable for employees and effective in practice. These principles can be used as a reference when developing a new AI policy or reviewing an existing one.
Keep AI policies simple and actionable
A good AI policy example translates general principles into clear instructions that employees can follow in practice. Employees should quickly understand what is allowed, what requires extra attention, and what is not permitted. Policies that remain too abstract often lead to uncertainty, which can result in either unsafe use or unnecessary avoidance of AI tools.
Practical examples help make the policy usable. For example, the policy can describe that AI may be used for brainstorming, drafting texts, summarizing documents, or supporting research.
Balance AI freedom with clear rules
A strong AI policy example also recognizes that AI tools are already part of everyday work. Employees often experiment with new tools on their own initiative. A policy that only focuses on restrictions can lead to uncontrolled use outside official systems.
A realistic policy provides space for responsible use while maintaining oversight. It explains which tools are approved and how new tools can be requested.
This encourages transparency and helps prevent uncontrolled use of external AI services. Employees are more likely to follow the policy when it supports their work instead of blocking it.
Create clear roles and responsibilities
Good AI policy examples clearly explains who is responsible for what. Employees should understand that they remain responsible for the quality and correctness of their work, even when AI tools are used.
It should also be clear where employees can go with questions or concerns. A designated contact person or team can support employees when they want to use new tools or when they are unsure about responsible use.
Make the AI policy easy to update
Lastly, a strong AI policy is written in a way that makes it easy to maintain over time. AI technologies and regulations change quickly, and policies need to evolve along with them. A structure that allows updates without rewriting the entire document helps keep the policy relevant.
Treating the AI policy as a living document makes it easier to introduce new tools and adjust guidelines when needed. Regular reviews and clear communication about updates help employees stay aligned with current practices.
