UK Officials Said AI Would Add £400 Billion to the Economy. That Figure Mainly Came From Google

Official economic projections for AI are now lower and more transparent about their origins.

UK government officials have acknowledged that a widely-cited figure of £400 billion as the potential economic benefit of Artificial Intelligence was based on a report commissioned by Google. The UK's AI minister, Kanishka Narayan, revealed in a parliamentary answer that the government's own more recent projections, considering AI adoption and data investment, estimate a benefit of £55 billion to £140 billion by 2030, with a central estimate of £120 billion. This lower figure acknowledges a slower rate of AI adoption than the consultancy firm Public First (now PF Global), which produced the Google-commissioned report, had assumed in its 2023 model. Despite ministers possessing the lower estimate since at least November 2025, government agencies continued to cite the £400 billion figure. The government has not formally withdrawn the higher figure, but this marks the first official instance of the two numbers being presented together, and the origin of the £400 billion estimate being disclosed.

The divergence between the £400 billion and £120 billion figures highlights a broader concern about the influence of industry funding on government policy and public perception of emerging technologies. When economic forecasts are based on research commissioned by specific companies, there's a risk that assumptions may be skewed to present a more optimistic outlook, potentially leading to policies built on exaggerated expectations. This situation underscores the need for government to rigorously vet external research and prioritize independent analysis to ensure evidence-based decision-making.

This development signals a market where the hype surrounding AI's economic potential is beginning to be tempered by more realistic assessments of adoption rates and tangible benefits. For policymakers and businesses, it suggests a shift towards more grounded strategies for AI integration, focusing on practical implementation challenges rather than solely on aspirational figures. Future economic planning and investment in AI will likely require greater scrutiny of data sources and a clearer understanding of the incentives behind economic projections.