Google’s UK pilot program has found that workers could save 122 hours per year—equivalent to three working weeks—by using AI for administrative tasks. This finding comes from the company’s “AI Works” initiative conducted in partnership with consultancy Public First.
“People wanted ‘permission to prompt’,” said Debbie Weinstein, Google’s Europe, Middle East and Africa president. “‘Is it okay for me to be doing this?’ And so giving them that reassurance was really important.”
The study suggests that giving workers explicit permission to use AI tools along with a few hours of basic training could double adoption rates. When workers received this support, their usage remained sustained months later.
The economic impact could be substantial. Google estimates these productivity gains could boost the UK economy by £400 billion ($533 billion) by 2030 if widely implemented and properly supported with training.
Addressing the Adoption Gap
The research exposed a clear adoption gap among different demographic groups. Two-thirds of workers surveyed had never used generative AI at work, with older women from lower socio-economic backgrounds particularly underrepresented.
Before training, only 17% of women over 55 used AI weekly and just 9% used it daily. Three months after receiving permission and basic training, these numbers jumped dramatically—56% were using AI weekly and 29% had made it a daily habit.
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Implementation Insights
The pilot was carried out across a small business network, educational trusts, and a union. It showed that psychological barriers often prevented workers from exploring AI tools, with many uncertain about whether using such tools was appropriate or allowed in their workplace roles.
Google has invested heavily in AI development, including its Gemini chatbot, potentially explaining its interest in promoting wider AI adoption in workplaces. The company frames these productivity gains as freeing workers from routine tasks to focus on higher-value activities that require human judgment and creativity.
For businesses considering AI implementation, the study suggests starting with clear communication that explicitly authorizes AI use for specific tasks, followed by focused training sessions that build user confidence through practical applications.
