UK business AI use doubled to 32%—but did productivity rise?
A representative government survey reached 3,503 businesses and found adoption had risen from 16% to 32%. Half of adopters reported a productivity increase, but the study did not independently measure output or prove AI caused the change.
The short version
- What happened
- Telephone interviews with 3,503 UK businesses found 32% used at least one AI technology, compared with 16% in the government's 2025 wave.
- Who it affects
- Workers may encounter AI first in administration, marketing and IT workflows. Training, oversight and job-quality evidence matter more than an adoption headline when judging whether that change helps them.
- What remains unproven
- 3,503 telephone interviews
Keep in mind
3,503 telephone interviews
50 follow-up interviews
Seven site visits
January–April 2026 fieldwork
Self-reported adoption and impact
No causal productivity estimate
No audited cost or output outcome
Source analysis · 1 linked source. Primary analysed source date: 29 October 2026.
Read the full report · 4 min The evidence, methods, implications and limitations
AI use spread quickly, mostly through accessible tools
AI use among UK businesses doubled in a year, according to a new government survey, but the evidence points to gradual workplace change rather than wholesale business transformation. Computer-assisted telephone interviews with 3,503 businesses found 32% were using at least one AI technology, up from 16% in the 2025 wave. Use remained uneven: 52% of larger firms reported adoption, as did 61% of information and communication businesses, compared with lower uptake elsewhere in the economy.
The survey ran from 7 January to 21 April 2026 and was supplemented by 50 follow-up interviews and seven ethnographic site visits. Natural-language processing and text generation dominated: 77% of firms using or planning AI cited large-language-model approaches. Administration was the most common function, reported by 81% of users or planners, followed by marketing at 71% and IT at 66%. Nearly half of respondents able to estimate 2025 AI spending reported no expenditure, consistent with free tools and features bundled into existing software.[1]
Reported gains were common, modest and not independently measured
Half of adopters said AI had increased productivity overall, while 71% reported workforce-productivity improvements and 60% more efficient or flexible processes. Those figures should not be read as measured output gains. Businesses described their own experience; the public summary does not link responses to audited productivity, revenue, hours worked or a comparison group. A firm adopting AI may also be investing in staff, software and process redesign, so the survey cannot isolate what caused any change.
Cost results underline that qualification. Twenty-four per cent of adopters reported lower operating costs, 64% no immediate financial effect and 9% an increase. Only 14% of businesses considered AI highly or critically important to operations. The findings therefore describe a technology spreading through support tasks while many firms remain exploratory. They do not establish that the national productivity problem has been solved or that an individual worker has become more secure, better paid or less burdened.[1]
The distinction that matters
What the survey measured—and what it did not
The same questionnaire can track reported adoption while remaining unable to prove a productivity cause.
Measured
3,503 businesses described AI use and experience
Representative self-reported snapshot
Compared
2026 answers were set beside the 2025 wave
Adoption rose from 16% to 32%
Missing
Link AI use to audited output, wages and costs
Causal productivity effect not established
Skills, proof and safety remain practical barriers
Limited skills, expertise or knowledge affected 67% of adopters and 78% of firms planning to adopt. Among non-adopters, 65% cited the absence of a clear business case or proven return. Accuracy and bias worried 56% of adopters and 60% of planners. Most businesses—81%—said people still applied some input or oversight to AI-generated outputs, especially where decisions carried higher stakes.
For workers and small firms, the useful message is not simply to buy another tool. Employers need time to redesign work, train staff, test accuracy and define who remains accountable. Confidence should change when future waves publish comparable weighting and uncertainty details and when administrative data connect adoption to output, wages, job quality, errors and business survival. Until then, the 2026 survey is strong evidence that reported adoption expanded sharply, not proof that AI caused economy-wide productivity growth.[1]