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Compare the pilot estimate with other studies and their limitations.
Research Guide · AI & automation
Understand where the 122-hour estimate came from, where AI can add work and how to measure the result on your own tasks.
The short answer
The 122 hours figure is real but narrower than it sounds. It comes from Google and Public First's 2025 UK pilots, where trained participants estimated that AI saved them the equivalent of 122 hours a year. It is self-reported by three pilot groups, not a measured result for UK business owners. Other studies find real but uneven savings, so measure your own tasks first.
Key facts
Who this is for. Owners and managers of UK small businesses who have seen the 122 hours figure and want to know what it means, where AI saves time and how to check it in their own business.
01
It comes from Google's AI Works report, published in April 2025 with the research firm Public First. Participants in three UK training pilots estimated their own time saved, which the report expressed as the equivalent of 122 hours a year. It is a pilot result, not a UK-wide measurement.
AI Works trained workers in three groups: education staff, small and medium business workers recruited through Enterprise Nation, and members of the Community trade union. Three months later, Public First asked them to estimate their time saved in an average week by choosing a band, such as 1–3 hours or 4–6 hours.
The report says workers in each group estimated savings equivalent to over 122 hours a year, 22% above Public First's modelled 100 hours. It gives group figures for education staff (2.9 hours a week, or 109 hours a year) and union members (2.1 hours a week). We could not find the calculation behind a single 122 figure, so treat it as a headline estimate.
| Often assumed | What the source says |
|---|---|
| A measured saving | Participants' own estimates, collected by survey. |
| A result for UK business owners | Workers in three pilot groups, not a random sample of owners. |
| What an untrained user would get | Everyone had training. The small business group volunteered and began with lower AI confidence than the average small business worker. |
| A saving for a whole business | An hours equivalent per worker, not a money figure. |
02
UK evidence is mixed. A cross-government trial found users estimated they saved 26 minutes a day. A Department for Business and Trade evaluation found small savings on written tasks but no robust evidence that they improved productivity.
The government's Microsoft 365 Copilot trial (30 September to 31 December 2024, 20,000 licences) found users estimated saving 26 minutes a day. This was self-reported: respondents chose time ranges and the report used the midpoints. The report could not identify how saved time was spent. DBT evaluated its own 1,000-licence pilot and found small savings on most tasks, the largest on written tasks, while scheduling and image generation took longer. It found no robust evidence that time savings improved productivity, though this was not a key aim.
| Study | Who and how | Result | Main limit |
|---|---|---|---|
| Google AI Works, 2025 | About 300 trained pilot participants, estimating after three months | 122 hours a year equivalent | Self-estimated, trained, not representative |
| Cross-government Copilot trial, 2024 | 20,000 licences, 7,115 survey responses | 26 minutes a day on average | Self-reported ranges |
| DBT Copilot evaluation, 2024 | 1,000 licences, diary study (32% response), interviews | Small savings, extra time on some tasks | No comparison group |
| Customer support study (NBER), 2023 | 5,179 support agents, tool introduced in stages | 14% more issues resolved per hour | One company's support work |
| METR trial, 2025 | 16 experienced developers, 246 tasks, randomised | Tasks took 19% longer with AI | Small sample, early-2025 tools |
03
AI saves the most time on text-heavy, repetitive tasks where a first draft helps: replying to messages, summarising documents and meetings, answering routine enquiries and moving information into a standard format. A person still reviews the result.
| Task category | Where time can be saved | What still needs a person |
|---|---|---|
| Email and message replies | First drafts of routine replies | Facts, prices, promises and tone |
| Meeting and call notes | Turning recordings into notes and actions | Names, decisions and numbers |
| Summarising documents and research | Condensing long reports or contracts | Checking against the original |
| Customer enquiries and FAQs | In the download ↓ | |
| Social posts and marketing copy | In the download ↓ | |
| Proposals, quotes and standard documents | In the download ↓ | |
| Data entry and reporting | In the download ↓ | |
| Scheduling and reminders | In the download ↓ | |
DBT reported the most pronounced savings for drafting documents, summarising research, searching for information and summarising meetings. In the cross-government trial, users reported savings of 24 minutes on drafting documents and 19 on creating presentations. In a 2023 MIT working paper, 444 professionals doing online writing tasks finished faster, and their work was graded higher, when randomly given ChatGPT. We found no UK study that measures a typical weekly saving per category for small businesses.
04
AI costs time when output needs heavy correction, when the task is already quick, when checking takes as long as doing it yourself, or when it creates extra work. Studies found slowdowns in scheduling, image generation and expert coding.
In the DBT pilot, extra time came mainly from Copilot being unable to produce high-quality output, or from tasks done only because the tool made them possible.
In METR's randomised trial, 16 experienced developers working on large open-source projects they contribute to took 19% longer when allowed to use AI tools. They had expected a 24% speed-up and afterwards still believed they had been 20% faster. The authors say it covers one kind of work with early-2025 tools and do not claim it applies to most software work.
05
Estimate it task by task: hours spent now, the share AI can draft, time to check and correct, and weeks worked. Then time the same task with and without AI, count checking time, and compare quality. The net saving is usually smaller than the gross saving.
Savings belong to tasks, not to a business as a whole, so subtract set-up, training, subscription and checking time. Do not rely on feeling faster: in METR's trial, developers who were slower believed they had been faster. DBT adjusted its diary estimates for outputs never used and for tasks done only because the tool existed.
Choose a task you do at least weekly, such as replying to quote requests.
Time ten jobs the usual way. Note the quality problems you normally see.
06
Not automatically. Saved time only adds value when it is used for something worth more, such as selling, serving customers or finishing work sooner. DBT found no robust evidence that time savings improved productivity, and the government trial could not tell how saved time was spent.
Be careful with money figures. A saving in pounds usually multiplies hours by an hourly rate, and both are estimates, so treat it as an upper bound.
Gains also vary by person. In the customer-support study, access to an AI assistant raised issues resolved per hour by 14% on average, with a 34% improvement for novice and low-skilled workers and minimal impact on experienced and highly skilled workers.
07
Check what data goes in before you start. The NCSC advises against putting sensitive information into public AI tools, and UK GDPR applies if you use personal data. Choose tasks that need no personal or confidential detail, then widen use once the terms are checked.
The NCSC says queries to public AI tools are visible to the provider, which stores them and is likely to use them to develop its services. The Information Commissioner's Office (ICO) says a business using a generative AI tool to draft client emails needs a lawful basis for the personal data involved.
Google's report recommends giving workers explicit permission to use AI and setting clear policies on AI tools.
08
Choose two repetitive text tasks, set the rules for what may be entered, measure a baseline, then trial AI for two weeks. Keep what saves net time and stop what does not. If a task needs your systems or customer data, get advice first.
Good first candidates are routine email replies, meeting summaries and summaries of long documents. They are text-based, frequent and easy to check. Leave customer decisions, sensitive data and professional advice until you have a track record.
Reeve Consult offers AI consultancy that looks at a specific workflow, the information it needs and where a person should check the output. It does not promise a time saving, and the steps above work without us.
The download
A research guide and practical measurement method for comparing task time, checking effort and output quality.
Compare the pilot estimate with other studies and their limitations.
Identify work where a useful first draft could reduce effort.
Count review time and compare quality before claiming a saving.
Frequently asked questions
Answers to common questions about this topic.
It is an average of participants' own estimates, expressed as a yearly equivalent per worker, from three pilot groups. The report does not present it as a figure for business owners or a UK average.
There is no fixed answer. The Google pilots measured three months after training, and both government trials ran for three months. Expect a learning period, so measure over several weeks and include learning time.
Start with frequent, text-based, low-risk tasks, such as routine email replies, meeting summaries and document summaries. DBT found written tasks showed the largest savings. Avoid scheduling at first, which took longer in its pilot.
No. Hours only become money if you use them for paid work, or avoid paying for the task. Figures in pounds usually multiply estimated hours by an assumed hourly rate, so treat them as upper bounds.
They measure different people, tasks and tools, and some rely on self-estimates while others time real tasks. Google's pilots used self-estimates and saw large savings. METR timed developers and saw a slowdown. Neither is wrong for its own setting.
Reliable enough to start from, not to send unchecked. In the DBT pilot, 22% of survey respondents said they identified hallucinations and 11% were unsure. Check names, numbers, dates, prices and claims before anything reaches a customer.
Sometimes, but UK GDPR applies to personal data. You need a lawful basis, must keep data secure and must check the supplier's terms. The NCSC advises not to put sensitive information into public tools. Start with tasks that need no personal detail.
Sources
Figures and rules on this page come from these sources. Check the original before relying on a number, as regulations and prices change.
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