Keeping supporter data safe when you use Artificial Intelligence
It is the question every charity asks first, and it should be. Here is how the tools handle your data, where the real risks sit, and the five things we put in place before anything connects.
Is Artificial Intelligence safe for a charity’s data?
It can be, if three things are true: the tool is one whose data terms you have read, it can only see what it needs, and a person checks what it produces. Trust concerns about Artificial Intelligence more than doubled among charities between 2025 and 2026, and were highest among organisations working with marginalised communities. The Beacon incident showed what a breach in a sector platform means for supporters. None of this is a reason to stop. It is the reason to do it properly.
Where the risk actually sits
People pasting data into personal tools.
The most common breach is not a connected system. It is a member of staff putting a case note or a donor list into a free chatbot on their own account. A short policy and approved tools fix most of this.
Tools connected with more access than they need.
A connector that can see every object and field will, one day, surface something it should not. Access has to be scoped, written down and tested before anyone uses it.
Outputs acted on without a check.
An Artificial Intelligence draft that goes to a supporter or a service user without a human reading it is a risk whatever tool produced it. A person stays accountable for everything that leaves the organisation.
How the tools handle your data, in plain words
Each vendor publishes its own data terms. These are the themes that matter to a charity. Plans and features differ, so we confirm the current terms for your set-up before anything is switched on.
Before anything is switched on, we confirm the current terms for your edition or licence, which models are on and where, and the features you will use.
The five things we put in place before anything connects
Step one
Data classification
A one-page list of what may go into an Artificial Intelligence tool and what never may: no service-user records, no safeguarding notes, no financial or health data unless a specific control covers it.
Step two
Scoped access
A named, read-only permission set or a dedicated integration identity so the tool sees only the objects and fields it needs. Where that is not possible for a tool, we say so and recommend a different route.
Step three
A short policy
Version one of an Artificial Intelligence policy and acceptable use rules for staff, written for your organisation, not copied from a template.
Step four
Human review
A rule that nothing produced by Artificial Intelligence reaches a supporter, service user or funder without a named person reading it.
Step five
A test that proves it
We show you a field the tool cannot see, and we keep the evidence. If it fails the test, it does not go live.
What should a charity’s Artificial Intelligence policy cover?
Half of charities have no policy. A good one is two pages and covers eight things.
Purpose: what the organisation wants Artificial Intelligence to do and not do.
Approved tools and accounts, and the rule against personal accounts for work.
Data that must never be entered, by category.
How a new use is proposed and approved, and by whom.
Human review of outputs, with the person accountable named.
Transparency with supporters, service users and funders about where Artificial Intelligence is used.
Training before use, for staff, volunteers and trustees.
Review every six months and after any incident.
We write a version one for you as part of Discovery and Planning. About Discovery and Planning
Frequently asked questions
Does Claude train on our data?
Can Artificial Intelligence see our safeguarding notes?
Where is the data processed?
Who is accountable if it gets something wrong?
Our commitments
We hold ISO 27001 and the Data Security and Protection Toolkit, our founder is our Data Protection Officer and Information Security Officer, and we use Artificial Intelligence ourselves under a published policy that says which tools we use, which data never goes in, and who stays accountable. After go live the same housekeeping continues through your Managed Service: access reviewed, connections audited, and the test repeated when tools change.