A Deloitte survey reveals one in six UK workers is personally paying for AI software to enhance productivity, signalling a shift towards unofficial adoption and raising concerns over security and policy gaps.
Britain’s workers are increasingly funding their own artificial intelligence tools to keep pace with the office demands of the technology, according to research from Deloitte. The consultancy said one in six employees is now paying personally for AI software used at work, at a collective cost approaching £1bn a year.
The findings point to rapid adoption that is outstripping formal company roll-outs. Deloitte’s inaugural GenAI Workforce Survey found that two-thirds of respondents had already tried tools including ChatGPT, Claude, Google Gemini and Microsoft Copilot, while nearly a quarter said they used them every day in their jobs. The survey, carried out by Ipsos among 25,000 workers, also found that 31% were using generative AI without their employer’s knowledge, a practice often described as shadow AI.
Deloitte said 17% of workers were paying for at least one GenAI tool themselves for work, suggesting many employees are taking a practical rather than a policy-led approach to adoption. Hayley McKelvey, Deloitte UK’s chief AI officer, said workers were showing they did not want to wait for permission to use GenAI, while Paul Lee, a Deloitte partner, said its use had already become part of everyday working life. He added that many employees were still using it for relatively simple tasks rather than more advanced work.
The most common uses were searching for information, drafting emails and producing summaries, which Deloitte said saved workers an average of 70 minutes a week. The broader picture suggests the technology is now well established in the UK workplace: Deloitte said more than 18 million people in Britain have used generative AI, up from 26% of adults in 2023 to 36% in 2024, and 74% of users believe it improves productivity. But the company has also warned that adoption without guardrails creates risk, especially where workers rely on systems their employers have not approved.
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