Digital Economy Dispatch #287 -- How Much AI Does the UK Government Actually Use?

How many AI and algorithmic systems are in use across the UK's central government? According to the government's own mandated transparency register, the answer is 131. That’s not an estimate, not a survey response, but the official record of every algorithmic tool that central departments have declared. The UK government has reported that it met its commitment to publish them all by the end of 2025.

Can that be true? It cannot, and the distance between that number and the reality needs to be explored.

When I worked on the National Audit Office's 2024 study of AI in UK government, our survey of 87 government bodies identified 74 AI use cases already deployed across departments and arm's-length bodies. That was autumn 2023, before the AI Opportunities Action Plan and before the current surge in adoption. If 87 bodies were already running 74 tools more than two years ago, a register today listing 131 across the whole of central government is not a measure of how much AI government uses. It is a measure of how much AI government departments are willing to write down. That 2023 count was itself conservative: the NAO survey deliberately excluded AI embedded by default in existing software and the ad-hoc use of public tools by individual civil servants, the very categories that have grown fastest since.

What the Register Shows

If you read through the register, the typical record is a calculator. Pension calculator. Budget planner. Mortgage repayment calculator. Interest calculator. Or perhaps a chatbot: Ask HMRC online, DVLA Contact Centre chatbot, GOV.UK Chat. Then an identity verification tool. Then a variety of dashboards such as a similar-schools clustering tool used for attendance reporting.

These are useful tools and worth publishing. They are also, almost without exception, the safest things to publish. A calculator that estimates your mortgage repayments is deterministic, low-risk and politically uncontroversial. A chatbot that surfaces existing guidance pages is really helpful and easy to defend. Publishing a transparency record is easy and quick.

What you will struggle to find in the register is the harder category. Tools that triage benefit claims for fraud signals. Tools that score immigration applications. Tools that prioritise tax investigations. Tools that assist police forces in risk assessment. These exist, and receive a great deal of comment. Other trackers, such as the Public Law Project's independent Tracking Automated Government register, identify a number of them. Most are not on the ATRS, either because they are explicitly exempt under the December 2024 scope and exemptions policy, because they sit just outside the in-scope organisations, or because no one has yet been compelled to declare them.

Unfortunately, a transparency register that operates only where the stakes are low is not offering a very meaningful picture of AI use in the UK public sector.

The AI Accountability Puzzle

The trajectory tells its own story. The ATRS became mandatory for central departments in February 2024. Through most of that year the register barely moved. By summer 2024 it held 9 records, and 23 by the end of the year. The compliance survey published alongside the NAO report found that 38 per cent of responding bodies reported never complying with the standard.

Then in January 2025 the Public Accounts Committee called in the Permanent Secretary at DSIT to give evidence and asked her directly why only 33 records had been published. Within twelve weeks the count had nearly doubled. By year end, against a public commitment to publish every in-scope tool by the end of 2025, it had reached approximately 125. The lesson is uncomfortably familiar. The mandate, as a piece of policy, did very little. What moved the needle was the prospect of being named in a select committee report.

This is not a particularly unusual finding. Soft policy mechanisms rarely change institutional behaviour without a clear tracking approach supported by a meaningful enforcement function. But it does suggest something specific about the architecture of AI accountability in the UK. If transparency relies on individual select committees noticing a problem in time to ask about it, the system has no general purpose mechanism for keeping pace with deployment. AI is being adopted faster than parliamentary scrutiny can be organised around it.

The Denominator is Unknown by Design

As a result, we don’t currently know how many algorithmic tools the UK public sector uses today. The UK government can declare the register complete only because it decides what counts as in scope. The current scope policy excludes a great deal: national security applications, broad analytical work, tools that affect "groups" rather than identifiable individuals, and more.

It also has no answer for the AI that is now arriving inside every commodity productivity tool the civil service procures. When a department buys Microsoft 365 with Copilot built in, no transparency record gets filed, even though every drafted email, summarised meeting and triaged inbox is shaped by an algorithmic system. Nor does it capture the shadow estate: the consumer tools civil servants reach for without sanction. A Microsoft survey of more than 2,000 UK workers found that 71 per cent had used unapproved AI at work, and there is no reason to assume Whitehall is the exception. The difference is that no one is counting how often it happens inside government, or what citizen data goes with it.

An effective public sector AI transparency regime would begin somewhere different. It would start with an independent inventory of deployed tools, conducted to a consistent definition, and use the register to make sense of that inventory rather than to constitute it. This is what we can see in other places. Amsterdam and Helsinki pioneered registers built from the systems their own administrations actually ran, and a shared transparency standard followed from that practice rather than preceding it. The Netherlands extended the same approach to national level, where the data protection authority is only now pressing for registration to become a legal requirement. The UK has gone the other way around, declaring the standard first and then hoping departments would follow.

Seeing is Believing

Want to see more on the UK government’s AI register? To offer greater insight and make this more concrete, I have published an interactive tracker that pulls every ATRS record live from GOV.UK, categorises them by tool type, and lets anyone browse, filter, and search the register. You can find it at futureofai.uk/atrs-tracker.html. It is not a replacement for the official register. It is meant as a critical companion to it. Take a look and let me know what you think.

If you work in or with the public sector, two questions are worth taking back to your own organisation. First, how many algorithmic tools is your organisation using, including the ones bundled inside the commercial software you have already paid for? Second, who in your organisation would notice if the answer to that question started to climb sharply?

A transparency standard that cannot answer those two questions is not yet doing the job it was built for.