How to Choose an AI Consultancy in the UK

Max Modlin · Founder · 14 October 2026

The short answer

Choose the consultancy that can show you AI systems it has built running in production, tells you who will do the work, is clear about your data and who owns the result, starts with a small project that proves its return, and stays to run what it builds. Everything else is presentation.

Why this choice is harder than it looks

Almost every firm now describes itself as an AI consultancy. Some are strategy practices that hand the build to someone else. Some are software agencies that added AI to their services page. A few build and run production systems every day. From the outside they can look the same, and the difference only becomes obvious months into a project.

The checklist below is the one we would use if we were buying. It works whether you are a manufacturer in Glasgow, a distributor in the Midlands or a professional services firm in London.

1. Ask to see what is running, not what was demonstrated

A demo shows that something can work on a good day. A production system shows that it works on every day, including the messy ones: the order that arrives as a photographed printout, the enquiry that needs four systems to answer. Ask which systems the firm has built that are live today, what they changed in numbers, and whether you can speak to the client.

2. Find out who actually does the work

Ask who will design, build and support your system, and how senior they are. A strong pitch team followed by a junior delivery team is a common pattern. With AI, the engineering judgement in the first few weeks decides whether the system holds up, so you want experienced people doing the work, not just selling it.

3. Check that they understand your operation

The hard part of most AI projects is not the model. It is the rules your best people carry in their heads: which customer address is right, which supplier always rounds up, when a job needs a second approval. Look for a firm that asks about those rules early and has worked in businesses like yours. Ask for examples from your own sector.

4. Be clear on data, security and ownership

Where will your data be processed and stored, and is any of it used to train someone else’s model?
Will the system use controlled access with only the permissions it needs?
Is every action logged and traceable to the document or request behind it?
Do you own the code, the prompts and the integrations, or are you renting them?

A serious consultancy answers these in writing before the build starts.

5. Keep the first project small and measurable

Large first phases are where AI budgets go to disappear. A better structure is a short, fixed-scope discovery that ends in a costed roadmap, followed by one process built in weeks with a result you can measure: minutes per enquiry, hours per bid, errors per month. If the first system does not pay back, you have lost weeks, not a year. See how AI consultancy is priced and how long implementation takes.

6. Make sure it fits the systems you already run

AI that sits beside your business, in a separate tool nobody opens, rarely survives. Ask how the firm connects to your ERP, mailboxes and portals, and whether anything has to be replaced. In most cases nothing should be. More on that in will AI work with our existing systems.

7. Ask what happens after go-live

Processes change, suppliers change their paperwork, and models improve. Software that is handed over and left ages quickly. Ask who monitors the system, how quickly problems are fixed, and how it gets better over time. The best answer is a named team that runs what it built.

Warning signs

A price before anyone has understood your operation.
Slides and demos, but no live systems or clients you can speak to.
A large first phase with outcomes described in general terms.
Vague answers on data, security or ownership.
No plan for who supports the system once it is live.

How we answer these questions

We are Agency AI, an AI consultancy of senior engineers based in Glasgow and working across Scotland and the UK. The systems we have built are running today: customer enquiries answered in ten seconds instead of eight minutes, bid first drafts in a tenth of the time, procurement documents matched in under five seconds. We are happy to walk through any of them. You can read the detail in our case studies.

Questions we are asked

How do I choose an AI consultancy?

Ask to see systems they have built that are running in production, find out who will actually do the work, check how they handle your data and who owns what they build, insist on a small first project with a measurable result, and ask what happens after go-live.

What questions should I ask an AI consultancy before hiring them?

Which of your systems are live today and what did they change? Who builds and supports ours? Where does our data go? Do we own the code and the integrations? What will the first project measurably change? Who fixes it when something breaks?

Should I choose a local AI consultancy?

Being close helps for discovery and go-live, when time on site matters, but proof and engineering depth matter more. A consultancy that has solved your kind of problem before is worth more than one that is nearby.

Is a large consultancy safer than a small specialist?

Not necessarily. What reduces risk is senior people doing the work, a small first project, and a firm that runs what it builds. Ask who will be on your project, not who is on the website.

What are the warning signs when hiring an AI consultancy?

A price before they understand your operation, demos instead of live systems, a large first phase, vague answers about data and ownership, and no plan for supporting the system after it goes live.

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