What happened
UK AI minister Kanishka Narayan admitted in a parliamentary response that the £400 billion figure previously used by the government to project AI's economic contribution was derived from a 2023 report commissioned by Google and produced by consultancy PF Global. The government's current internal estimate places the benefit between £55 billion and £140 billion, with a central estimate of £120 billion. This admission marks the first recorded instance of the government explicitly attributing the higher figure to a private industry commission and contrasting it with its own projections.
UK AI minister Kanishka Narayan responded to a parliamentary question by clarifying the origin of the £400 billion figure that had been used by UK government departments for nearly two years. He stated that this number was drawn from a publicly available 2023 report commissioned by Google and produced by the British consultancy PF Global (formerly Public First).
Narayan disclosed that the government's own more recent assessment estimates AI's contribution to the UK economy by 2030 to be between £55 billion and £140 billion, with a central estimate of £120 billion. He described this internal estimate as 'hugely uncertain' but noted it was significantly lower than the previously cited £400 billion figure.
The admission came after WIRED reported that the government had been using the Google-commissioned figure for almost two years under two different administrations. Although ministers had access to the lower internal estimate since at least November 2025, agencies like Skills England continued to publish the higher number until four months later. This parliamentary answer is the first recorded evidence of the government placing the two figures side by side and acknowledging the private commissioning of the higher estimate.
Jonathan Dupont, head of economics at PF Global, explained the disparity by citing the government's slower rate of AI adoption compared to the assumptions in the 2023 model. He noted that while the overall potential of the technology remains unchanged, the central estimate for likely achievement by 2030 is now closer to the government's number due to practical adoption rates.
Why it matters
This revelation exposes a significant gap between public-facing AI economic narratives and internal government assessments, raising concerns about the influence of industry-funded research on policy formulation. The discrepancy of nearly £300 billion challenges the reliability of the data used to justify public investment and digital transformation strategies. It highlights a broader issue of 'hype' in AI policy, where precise-sounding figures may be driven by corporate incentives rather than independent analysis. The incident underscores the need for transparency in how governments source and validate economic projections for emerging technologies, as these figures directly influence budget allocations and public trust in digital initiatives.
The incident highlights a critical tension between industry-promoted economic projections and independent government assessments. The use of a Google-commissioned report for high-level policy messaging raises questions about the independence of data used to justify public spending and digital transformation strategies.
Dame Chi Onwurah, chair of the Commons Science, Innovation and Technology Committee, warned that overstating the benefits of technology risks undermining the case for change due to 'hype.' She emphasized the need for the government to be realistic and transparent with the public about potential savings and benefits.
Lord Holmes of Richmond, who had previously questioned the origins of the £400 billion claim without receiving a response, criticized the delay in clarification. He stressed that robust data is critical for the deployment of billions of pounds in public funds, and that the government should have addressed the discrepancy sooner.
Sumedha Deshmukh of the Ada Lovelace Institute pointed to a wider pattern where industry-funded research shapes economic narratives. She urged the government to test the numbers it is given, fund independent research, and measure whether promised gains are actually delivered, rather than relying on figures with built-in incentives.
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What to watch next
Monitor whether the UK government formally withdraws or updates the £400 billion figure in official publications and policy documents. Watch for reactions from other government agencies, such as Skills England, which was still using the outdated figure recently. Observe if this incident triggers broader parliamentary inquiries into the sourcing of economic data for AI policy and whether independent research funding is increased to counterbalance industry-commissioned studies.
Observe if the UK Cabinet Office or other departments issue formal corrections or updates to official documents that still reference the £400 billion figure. The continued use of outdated data by agencies like Skills England suggests a lag in policy alignment that may require administrative intervention.
Watch for further parliamentary scrutiny regarding the sourcing of economic data for AI policy. The admission may lead to broader inquiries into how other industry-commissioned reports are used in government decision-making processes.
Monitor the response from Google and PF Global regarding the independence of their research. While PF Global stated their judgments were independent, the commissioning by a major AI player may continue to influence public perception and policy debates.
Look for shifts in the UK government's approach to AI economic forecasting, potentially including the adoption of more conservative estimates or the commissioning of new, independently funded research to provide a clearer baseline for policy.