A written AI policy
protects the business before anything goes wrong.
Practical, plain-language AI policy development for how staff use AI tools, what data they can touch, and what happens when something goes wrong.
Many businesses have staff already using consumer AI tools informally, without any written guidance on what is and is not appropriate, which data can be shared with them, or what happens if something goes wrong. AI policy development addresses this directly with a short, plain-language document covering exactly these questions, specific to your business rather than copied from a generic template.
This is distinct from AI governance for systems you build. Policy development specifically covers staff use of AI tools in their day-to-day work, including tools your business did not build itself.
The businesses that address this now are building an advantage competitors will spend years trying to close.
Without a written policy, staff make individual judgement calls about what is appropriate to share with an AI tool, which creates inconsistent, unmanaged risk, particularly around sensitive customer or business data.
A clear policy also protects staff themselves, giving them a straightforward answer to what is and is not acceptable, rather than leaving them to guess and potentially get it wrong.
As AI tool use becomes more visible to customers, regulators, and insurers, having a documented, sensible policy is increasingly something a business needs to be able to show, not just something nice to have internally.
How it actually works: We work with you to understand how staff are already using AI tools, define clear, practical rules around data sharing and appropriate use, and deliver a plain-language policy document staff will actually read and follow.
A structured process, not a black box.
Current use assessment
We assess how staff are already using AI tools in practice, formally or informally, before writing anything.
Risk identification
We identify the specific risks that matter for your business, particularly around data sensitivity.
Policy drafting
A clear, plain-language policy is drafted covering appropriate use, data boundaries, and accountability.
Review and refinement
The draft is reviewed with relevant stakeholders and refined until it is genuinely practical, not just legally cautious.
Rollout and training
The policy is rolled out with a short briefing so staff genuinely understand and follow it, not just receive it.
What's technically involved
- A plain-language policy document, not a legal template nobody reads
- Clear rules on what data can and cannot be shared with AI tools
- Defined accountability for AI-assisted work
- A specific process for what happens if something goes wrong
- A short staff briefing to support genuine understanding and adoption
Where this sits in a wider AI strategy.
This work often sits alongside a broader AI governance engagement for systems you build yourselves, but focuses specifically on staff use of external and consumer AI tools in daily work.
Common questions
Do we need this if staff are only using AI tools informally?
Yes, arguably especially so. Informal, ungoverned use of AI tools with business data is exactly the situation a clear policy is meant to address before it becomes a genuine problem.
Will this stop staff from using AI tools altogether?
No, and that is not the goal. A good policy defines what is appropriate rather than banning AI tools outright, since outright bans tend to simply push usage underground and out of sight.
How long is a typical policy document?
Short and specific is the goal, usually a few pages covering the practical questions that actually matter, rather than a long legal document nobody will read in full.
Does this cover specific tools like ChatGPT by name?
It can, where relevant, alongside general principles that apply regardless of which specific tool staff might use.
How often should the policy be reviewed?
At least annually, or sooner if your business starts using AI in a meaningfully new way, since both the technology and your own usage patterns tend to change.
AI Policy Development works best alongside a strong technical foundation: Technology Partner, Custom Software.
Let's find out where this fits in your business.
A short conversation is usually enough to tell whether there is a real opportunity here.