The £400 billion figure the UK government attached to AI adoption came from a 2023 report commissioned by Google and produced by Public First, AI minister Kanishka Narayan said in a written parliamentary answer on 26 October. The government’s own central estimate is £120 billion, about 30% of that figure, by our arithmetic.
Narayan gave the government’s range as £55 billion to £140 billion of added UK gross value added in 2030, and said the estimates are “hugely uncertain”.
Business Pill · Forecast vs Commitment
An evergreen Business Engineer explainer on the difference between a forecast and a commitment. It teaches the general idea only and does not discuss the UK, Google or any estimate in this piece.
The key insight: AI minister Kanishka Narayan says the £400 billion AI figure came from a 2023 Google-commissioned study by Public First, and gives the government’s own central estimate as £120 billion of added gross value added in 2030, about 30% of the £400 billion figure, by our arithmetic.
MP Dr Ben Spencer asked for the evidential basis of the statement in the AI Opportunities Action Plan that AI adoption could add £400 billion to the economy by 2030.
Narayan answered for the Department for Business, Innovation, Science and Trade. The answer reads: “The £400 billion figure was drawn from a publicly available 2023 report commissioned by Google and produced by Public First, which estimated that generative AI tools could create over £400 billion in value for the UK economy by 2030.”
The answer adds that “The Government has since made a more recent assessment”. That assessment says AI adoption and data investment could add 0.4 to 1.3 percentage points to UK productivity growth, which the answer puts at £55-140 billion of gross value added in 2030. “The central adoption estimate is £120 billion,” Narayan wrote.
The figure the minister traced to a 2023 Google-commissioned study by Public First, against the government’s own 2030 range and central estimate, from UK Parliament written answers 32092 and 30469. The 30% is our arithmetic; the two measures differ.
The Earlier £47bn Figure
In a separate answer on 23 October, Narayan said the “previous £47 billion estimate” in the Action Plan was a UK government calculation based on the IMF’s World Economic Outlook of April 2024. The same answer says the OECD estimates that AI adoption could add 0.4 to 1.3 percentage points to the UK’s annual labour productivity growth over the next decade.
When Spencer asked on 27 October how the £120 billion central estimate was derived, Narayan’s 4 November answer referred Spencer back to the 23 October answer.
How Far Apart the Figures Are
By our arithmetic, the government’s £55-140 billion range is about 14% to 35% of the £400 billion figure, and the £400 billion is about 3.3 times the central estimate.
WIRED reported the answers on 4 November, according to Resultsense’s summary of its report. That summary says ministers had the lower estimate from at least November 2025, while Skills England was still publishing £400 billion four months later.
The same summary says PF Global, as Public First is now called, defends its research as independent. It says the 2023 model assumed faster adoption than has happened, and that its central estimate for 2030 is now “much closer to the Government’s number”.
As we read the answers, the government now gives two numbers on the record, a study figure it attributes to Google’s commission and its own range of £55-140 billion.
As we read the figures, the gap between them is about 3.3 times at the central estimate, by our arithmetic, though the two measure different things.
As we read the follow-up answers, the derivation of the £120 billion central estimate points back to the OECD productivity range cited on 23 October.
Kanishka Narayan, written answer 32092
“These estimates are hugely uncertain, but this would be the equivalent of adding £55-140 billion to UK GVA in 2030”
Three Implications
FOR READERS OF UK AI CLAIMS The minister attributes the £400 billion to a 2023 study commissioned by Google and produced by Public First.
FOR THE GOVERNMENT’S OWN NUMBER The central adoption estimate is £120 billion, within a £55-140 billion range for 2030.
FOR THE STUDY’S AUTHORS PF Global says its central estimate for 2030 is now much closer to the government’s number, according to Resultsense’s summary of WIRED.
The framework says: “Read one number and legal is barely touched; read the other and a sixth of its work output already runs through the agentic surface.”
As we read it, the UK’s two AI figures are a case of which number gets read. The framework does not discuss the UK, Public First or government estimates.
What Is Not Established
The two figures measure different things: the 2023 study counted value that generative AI tools could create by 2030, while the government’s range is added gross value added in 2030. The answers do not say the £400 billion figure was wrong or withdrawn. We have not read WIRED’s article directly; the Skills England timeline and PF Global’s response rest on Resultsense’s summary.
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The UK’s AI minister says the £400 billion figure came from a 2023 Google-commissioned study, and gives the government’s central estimate as £120 billion, about 30% of it by our arithmetic.
A note on sourcing. The minister’s words and figures are from UK Parliament written answers 32092, 30469 and 38587, read on 5 November 2026. The percentages and multiples are our arithmetic. WIRED’s reporting rests on Resultsense’s summary.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
