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AI Governance Services for UK Organisations Deploying Artificial Intelligence

Most organisations did not decide to adopt AI. It arrived, tool by tool, in marketing, HR and customer service, usually without a policy behind it. AI governance is how you regain control: a single framework covering which tools are approved, who signs them off, how risk is assessed and what happens when something goes wrong. We build that framework around how your organisation actually works, so it is used rather than filed.

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AI governance is a data protection problem before anything else

The UK has no single AI Act. That leads people to assume there is nothing to comply with, which is the most expensive misreading in this area. Almost every AI risk your organisation faces is already regulated under UK GDPR: the lawful basis for training or prompting with personal data, transparency about automated processing, fairness and bias, data minimisation, and international transfers when a model is hosted overseas. The ICO regulates all of it today. If your organisation operates in the EU or offers services there, the EU AI Act applies on top. Governance is what turns those overlapping duties into decisions your teams can actually make.

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Why organisations bring us in for AI governance

Certified privacy professionals, not general AI consultants

AI governance sits on data protection law. Your framework is built by experienced, certified professionals with CIPP/E, CIPM, FIP and GDPR Practitioner qualifications among the team, so it holds up when the ICO asks how you reached a decision.

A framework proportionate to your actual risk

A twenty person charity does not need the governance structure of a bank. We tier your AI uses by real risk and build only the controls those tiers justify, so you are not maintaining a framework designed for somebody else's organisation.

We find the AI you do not know about

Shadow AI is the norm, not the exception. We start by establishing what is genuinely in use across your teams, because a policy written against an imaginary tool list protects nobody.

It connects to your wider compliance position

Your AI framework should reference the same DPIA process, breach procedure and records of processing you already run. We integrate rather than bolt on, so you end up with one compliance position instead of an AI silo that quietly goes stale.

A named lead you can actually speak to

You will have a named lead practitioner as your point of contact throughout, not a ticket queue. Governance work involves judgement calls, and those are better made in a conversation than in a form.

When AI goes wrong, and what to do first

AI incidents rarely look like classic breaches. They look like an employee pasting client data into a consumer chatbot, a model producing a discriminatory outcome in recruitment, or a supplier quietly changing its training terms. Each needs a different response, and the seventy two hour clock for reporting a personal data breach to the ICO does not pause while you work out which one you are dealing with. We build AI incident scenarios into your existing breach procedure, with named decision makers and a triage step that tells you quickly whether you are dealing with a reportable breach, a policy failure or a supplier issue.

How an AI audit works

Find the AI in use

We map the AI software genuinely active across your business, including the shadow tools nobody declared, and flag where personal data is being entered.

Check the legal position

We review vendor contracts, data processing agreements and opt out settings, confirm whether suppliers train public models on your data, and identify which workflows need a DPIA.

Fix what matters first

Findings come back as a prioritised risk matrix with the governance documents that follow, so you know what to deal with this month and what can wait.

What you receive

An AI system register, drafted DPIAs meeting Article 35, a tailored AI acceptable use policy, a vendor DPA gap analysis with the remediation requests to send, and a prioritised action plan for your leadership team.

What an AI governance framework contains

A framework worth having is short enough to be read. Ours typically covers an inventory of AI tools in genuine use, including the ones nobody approved, a risk tier for each use case, a clear approval route for new tools, defined roles for who owns AI decisions, the trigger points for a DPIA, rules on what data may and may not be entered into a model, supplier and model due diligence, and a route for staff to raise concerns. It should sit alongside your existing data protection policies rather than duplicating them.

Who needs an AI governance framework

Not every organisation using AI needs the same level of structure. If you have a handful of staff using ChatGPT with no customer data involved, a policy and some training will cover you. If you are processing personal data through AI, making automated decisions that affect people, using AI in recruitment, health, finance or education, or selling into the EU, you need a documented framework with named owners and a defensible audit trail. The gap we see most often is organisations in the second group operating as though they are in the first.

AI governance questions we get asked

What is AI governance and why does it matter?

AI governance is the set of policies, roles and controls that determine how your organisation adopts and uses AI. It matters because accountability under UK GDPR sits with you, not with the AI vendor. If a tool your staff use processes personal data unlawfully, the ICO will look at your decision making, your documentation and your oversight. Governance is what you show them. Where you need the policy itself drafting rather than the whole framework, we offer that as AI acceptable use policy creation.

Does the UK have an AI law we need to comply with?

There is no single UK AI Act. The UK has taken a regulator led approach, so existing law applies through existing bodies, with the ICO covering AI that involves personal data. In practice, that means UK GDPR, the Data (Use and Access) Act 2025 and ICO guidance are the rules that bind you today. If you operate in or sell into the EU, our EU AI Act guide explains what applies to you.

What is the difference between AI governance and a DPIA?

A DPIA assesses one specific processing activity. Governance is the layer above it that decides which activities need a DPIA in the first place, who approves them and how they are reviewed. Most organisations that come to us have done a DPIA or two without a framework, which means the assessments happen wherever somebody happened to remember. Where an assessment is needed, we produce it as part of the framework. See DPIAs for AI systems.

How do we deal with staff using AI tools we have not approved?

This is known as shadow AI, and it is the single most common finding in the discovery work we run. Start by finding out what is actually being used, without treating it as a disciplinary exercise, because people hide tools when they fear the answer. Then, approve a small number of safe options so there is a legitimate route, and set clear rules on what may never be entered into any model. A policy that bans everything gets ignored. An AI Acceptable Use Policy is usually the practical output here. Where the tool in question is ChatGPT or a similar model, see our ChatGPT and LLM compliance services.

What is an AI data privacy audit?

An AI data privacy audit is a review of how your organisation collects, inputs and processes personal data using artificial intelligence and machine learning software. It identifies legal risks, checks compliance against UK data protection law and establishes whether third party vendors are handling your data acceptably. It is normally the first stage of a governance engagement rather than a separate service, and it is how we find the tools nobody declared.

What should we do if an AI tool causes an incident?

Triage it first. Establish whether personal data left your control, whether an individual was affected by an automated outcome, and whether a supplier changed something. If personal data has been compromised, the ICO reporting clock applies as it would for any breach. Build these scenarios into your existing breach procedure in advance, because working out ownership during an incident is how deadlines get missed.

How long does it take to put a framework in place?

For a small or medium organisation, typically four to six weeks from discovery to a signed off framework, depending on how many tools are in use and how quickly we can get time with the people who own them. Larger organisations with multiple business units take longer.

Can you work with our existing IT or security team?

Yes, and it works better that way. Your IT team usually knows what is technically deployed, and we bring what the law requires of it. Where you already hold ISO 27001 or similar, we align the AI framework to the structures you have rather than creating a parallel set of documents.