Google says AI power users drive UK productivity gains
A widening skills divide in AI use risks leaving most of the UK workforce behind despite rapidly increasing adoption rates.
Workplace AI adoption in the UK has more than doubled over the past year, reaching 73%, according to a new Google report. However, the benefits remain uneven, with a small group of advanced users seeing significantly stronger career outcomes than the wider workforce.
The report categorises workers into four groups: AI Spectators, who have not yet engaged with the technology; Experimenters, who use basic AI functions; Practitioners, who use AI regularly; and AI Trailblazers, who apply it in advanced and innovative ways.
Although AI Trailblazers account for just 15% of users, they report significantly better outcomes, including faster promotions, larger pay increases and substantial weekly time savings.
The report found that advanced users outperform other workers across several indicators, including promotions, performance reviews and salary growth. However, differences in adoption across age, gender and geography suggest that unequal access to AI skills could widen existing labour market disparities.
Google argues that closing this gap will require greater investment in AI literacy, organisational support and workplace culture. Initiatives such as national upskilling programmes and diagnostic tools are intended to help workers progress from basic experimentation to more advanced AI use, supporting broader productivity growth.
Why does it matter?
The findings suggest that simply adopting AI is not enough to generate widespread economic benefits. The greatest productivity and career gains are concentrated among workers who integrate AI deeply into their daily work, highlighting the importance of skills development and organisational support.
The report also points to a growing policy challenge. If access to advanced AI skills continues to vary across demographic groups and regions, AI could widen existing inequalities in the labour market. Expanding AI literacy and helping more workers move beyond basic use may therefore be as important as increasing adoption itself.
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