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Poor workforce health is associated with an estimated £241 billion in lost UK output each year, according to Vitality and RAND Europe’s 2026 Global Health and Productivity Index. That is not a bill for sick days alone, and it does not show that AI is making the cost rise. Evidence points to possible AI-related productivity gains and workplace risks, but the effect of AI on this £241bn estimate has not been established.
What the £241bn estimate measures
Vitality says its research with RAND Europe estimates that poor workforce health costs the UK economy £241bn a year in lost output, equivalent to about 8% of GDP. The figure is an estimate of work and output affected by ill health, rather than a direct count of money spent on sick pay or the value of days when employees are absent.
A key part of the picture is presenteeism: working while a health problem affects someone’s ability to perform. An employee may be at work but less able to concentrate, make decisions or complete tasks. That lost capacity is harder to see than an absence record, but it can still reduce output. The index estimates 30.3 additional lost-productivity days per year for an employee in a high mental-health wellbeing risk group. That is a finding about that risk group, not the average for every UK employee.
Absence remains one part of the wider cost. A Department for Work and Pensions (DWP) technical note, updated on 31 March 2026, cites a UNUM study estimating four to nine lost productive days per employee per year due to presenteeism. The note uses that range in its own estimate of employer costs; it should not be treated as a nationwide count of days directly observed by government.
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How the £241bn figure differs from other UK estimates
Other large estimates concern different populations and costs. Their similar headline values do not mean they measure the same thing, and they should not be added together.
| Estimate | Scope and components | Period and method |
|---|---|---|
| £241bn a year | Lost output associated with poor workforce health; Vitality highlights presenteeism. | Vitality and RAND Europe’s 2026 estimate, published in October 2026; expressed as an annual cost and about 8% of GDP. |
| About £85bn a year | DWP estimate of employer costs of poor workplace health: £10bn sick pay, £47bn lost output when employees cannot work, £21bn presenteeism, and £7bn conflict resolution, litigation and recruitment. | DWP Keep Britain Working technical note, updated 31 March 2026; employer costs, with presenteeism informed by the cited UNUM estimate. |
| About £212bn a year | DWP estimate of health-related economic inactivity: £132bn lost output, £45bn health-related benefits, £37bn lost output from unpaid carers and £2bn additional NHS costs. | Published by DWP in September 2026; combines costs across output, benefits, unpaid care and NHS spending. |
| £240bn–£330bn | Estimated cost of working-age ill health and disability that prevented people from working. | DWP’s 2025 publication estimates the position in 2022 as the gap between actual and potential output. |
The boundaries matter. For example, the £85bn figure includes employer costs such as sick pay, while the £212bn estimate includes benefits, unpaid-carer output and NHS costs. The £240bn–£330bn range refers to a specific reference year and a comparison between actual and potential output. Differences in scope, methods and dates mean none is a like-for-like alternative measurement of the £241bn figure.
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DWP also reports that around 300,000 people with a health condition leave work each year. This illustrates a separate concern from reduced productivity among people who remain employed: ill health can affect whether people are able to stay in work at all.
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What the evidence says about AI and work
The claim that the £241bn cost “may only get worse as AI takes over” goes beyond the available evidence. A January 2026 UK government assessment says AI can improve productivity in some tasks and occupations, but it remains uncertain whether those gains will scale across firms or the wider economy. The assessment also notes changes in hiring patterns in occupations exposed to AI, while cautioning that it has not established AI as the cause.
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That uncertainty reflects different stages of change. A tool improving performance on a particular task does not by itself show that a whole firm will become more productive; even firm-level gains do not settle what will happen to employment across the economy. Evidence at one level should not be presented as proof of an outcome at another.
AI’s impact on workers is not limited to whether a task can be automated. International Labour Organization materials published in April and June 2026 identify potential psychosocial risks such as intrusive workplace surveillance, work intensification, reduced autonomy and privacy concerns. They also describe possible efficiency and productivity benefits. The ILO characterises early gains as uneven and often not yet visible in measured output, earnings or employment.
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These findings make a conditional case: how AI is introduced and managed could affect job tasks, work organisation and wellbeing. They do not quantify an AI-driven increase in the £241bn estimate, or establish that such an increase is inevitable. Conversely, the possibility of productivity improvements does not prove that AI will reduce the health-related cost.
What employers and workers can take from the figures
The estimates point to a measurement problem as well as an economic one. Tracking absence alone can miss employees who are present but struggling to work effectively. An employer considering workplace health should therefore distinguish absence from presenteeism and from people leaving work, rather than treating all three as a single measure. The DWP’s employer-cost breakdown shows why: costs include sick pay and absence-related lost output, but also presenteeism and the expense of conflict resolution, litigation and recruitment.
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For AI adoption, the evidence supports watching both performance and working conditions. A productivity claim should specify whether it concerns a particular task, an entire firm or the wider economy. Employers should also consider whether new systems change monitoring, workload, autonomy or privacy, the areas of concern identified by the ILO. Those checks do not predict the eventual economic effect; they help avoid assuming that a technical capability automatically translates into better output or better work.
The strongest conclusion is therefore narrower than the headline forecast: poor health is linked to a very large estimated loss of UK output, with presenteeism an important part of the account. AI may reshape productivity and the experience of work, but current evidence does not show that it is responsible for the £241bn cost or that it will make that figure rise.
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