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AI is becoming more common at work, but PwC’s 2026 findings suggest adoption does not automatically mean a lighter workload. In the UK, 56% of workers said they had used AI at work in the preceding year. Among AI users, many reported better-quality work, while substantial shares also said their work had become more complex or their workload heavier.

What PwC’s 2026 findings say about AI at work

PwC UK’s 2026 Hopes and Fears findings show that 56% of UK workers reported using AI at work in the past year, compared with 64% globally. The figures describe workers’ reported experiences; they do not, by themselves, show that AI caused a change in workload or work quality.

Among AI users, 70% said AI improved the quality of their work. At the same time, 45% said their work had become more complex and 44% reported a heavier workload. These three percentages refer to AI users, not to all UK workers.

AI use is not evenly distributed across roles

PwC reports that AI use among UK non-managers rose from 24% to 35% over the previous twelve months. That increase points to growing use outside management, but it also highlights why a single workforce-wide adoption figure can obscure differences between job levels.

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The report page does not provide the sample size, field dates, detailed wording of the relevant questions or subgroup bases for these specific findings. The percentages should therefore be read as survey responses, not as precise measures of how often AI is used in each occupation or as a causal estimate.

Why better work quality can coexist with more work

The findings capture two sides of AI use: users often perceive an improvement in work quality, yet many also report added complexity or workload. A tool may assist with parts of a task without removing the surrounding work, or it may change what a role requires. The figures do not identify which explanation applies to individual respondents, so they should not be treated as proof that AI itself created the extra work.

That distinction matters for employers assessing results. Counting AI access, usage or output alone will not reveal whether a process has been redesigned, whether work has shifted elsewhere, or whether employees are absorbing new tasks alongside existing responsibilities.

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PwC’s prescription: redesign work around real roles

PwC’s recommendation is not simply to push AI into more teams. Claire Reid, PwC UK’s Chief Technology and Innovation Officer, says organisations should connect AI to the right problems and job roles, give people opportunities to experiment and learn, involve them in shaping its use, and put safeguards in place. She argues that workers need to see how AI applies to their own work for confidence and value to grow.

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For leaders, that means assessing AI against the work it is meant to change, rather than treating adoption as the goal in itself. Useful questions include:

  • Does the use case address a meaningful task in the role, rather than add a disconnected tool?
  • Do workers have time and support to learn, experiment and help shape the workflow?
  • Are workload and task complexity being tracked alongside work quality and productivity?
  • Do measures distinguish higher output from genuine workflow redesign?
  • Are appropriate safeguards in place for the work and information involved?

PwC says leaders need measures that distinguish productivity gains from workflow redesign. That is a practical way to test whether AI is changing how work gets done—or merely adding another step to an existing process.

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