An external AI usage policy is the public statement you share with clients,
prospects and the general public to explain how you use AI in your content and services.
It builds trust by being clear about when AI assists you, what safeguards you have in place,
and who is ultimately accountable.
Quick Disambiguation: External vs Internal AI Policies
- External policy – what your clients and readers see. Explains AI in blogs,
reports, chatbots, data analysis, etc. - Internal policy – rules for your team on how to use AI tools day to day.
Covers licence management, security settings, acceptable use and so on.
A good external policy
- Defines the scope – what you do vs what you don’t do with AI
- Explains transparency – how you disclose AI involvement
- Shows human oversight – who reviews and signs off
- Details data protection and compliance
- Commits to ethical principles – fairness, safety, accountability
- Specifies review frequency and update process
Template (copy and adapt)
AI Usage Policy
Policy last updated: [YYYY-MM-DD]
Company: [Your Company Name]
Definitions
- AI-assisted: AI supports your work; a human makes the final call.
- AI-generated: AI creates content with minimal human edits.
Purpose
This policy explains how you use AI tools in your client-facing content and services.
Audience
This policy is for your clients, prospects and the general public.
Regulatory Context
In line with the EU AI Act, UK Data Protection Act and GDPR as applicable.
Scope of AI Use
You use AI for:
- Content creation: [e.g. whitepapers, blog drafts, chatbot replies]
- Decision support: [e.g. data analysis, risk scoring, tailored recommendations]
You do not use AI for:
- [e.g. final legal advice, confidential strategy decisions]
Transparency & Disclosure
How you disclose AI involvement:
- [e.g. banner on each page, footnote in articles, link to this policy]
Sample disclaimers:
“This content was developed with AI-assistance and reviewed by [role].”
“This chat is powered by an AI assistant – you can request a human at any time.”
Policy ownership:
[Role or person] maintains and updates these disclosures.
Human Oversight & Quality
Quick review checklist:
- [ ] Generate AI draft
- [ ] Fact-check by [role]
- [ ] Run bias scan
- [ ] Final sign-off by [role]
Error handling:
Log, correct and communicate any mistakes or bias as soon as they occur.
Data Privacy & Compliance
Data used: [e.g. anonymised client data, public datasets]
Protection measures: anonymisation, encryption and secure storage
Consent: obtain explicit consent before sensitive data enters an AI system
Compliance: GDPR, UK Data Protection Act, EU AI Act
Explainability & Accountability
How you explain AI outputs:
“This risk score reflects factors X and Y. It was reviewed and approved by [role].”
Responsibility:
You (not the AI vendor) are fully accountable for any AI-derived output.
Ethical Principles
- Fairness: test for and mitigate bias quarterly
- Transparency: publish an annual summary of AI use
- Safety: avoid AI in high-risk scenarios without controls
- Accountability: ensure human experts oversee all AI outputs
Review & Updates
Review frequency: every [e.g. 12 months] or after major AI or regulatory changes
Change notifications: note updates here and share via [e.g. blog post, newsletter]
Policy owner: [Role or person]
Questions or feedback? Contact us at [email@yourcompany.com].
- Copy the entire section above
- Replace placeholders like
[Your Company Name]and[role]with your details. - Update the “Policy last updated” date each time you revise.
- Publish the policy page and link to it from your footer or site menu.
