在过去两年中，英国政府一直告诉英国公众，由于AI的帮助，该国可以获得4000亿英镑的经济提振，这个数字旨在平息人们的担心，即该技术将导致失业，甚至经济崩溃。
但英国AI部长上周承认，这个数字大大高于政府的实际预测，因为政府透露，评估完全来自Google委托的一份报告，英国自己对AI经济效益的估计还不到4000亿英镑的三分之一.n.
AI部长卡尼什卡·纳拉扬(Kanishka Narayan)在回答议会关于这个问题的一个问题时，称认为AI的通过和数据投资到2030年可以给英国经济增加550亿至1400亿英镑，使得中央估计达到1200亿英镑。 但是，即使这一“最近评估”，称也是一种“非常不确定”的估计。
Narayan 称的400b英镑数字“取自Google委托公众提供的、由Public First公司编写的2023年报告”，一家英国咨询公司现在称为PF Global。
对WIRED关于数字差异的质疑，PF全球经济学主管乔纳森·杜邦(Jonathan Dupont)，称的悬殊部分是由于他们认为政府缓慢采用AI. “大赦国际是一个非常迅速移动的技术，随着我们学到更多的东西，我们不可避免地必须更新我们模型背后的假设。 与我们的旧模式相比，政府使用的数字假定采用率比2023年创建的我们的模式中可能回顾的要慢得多。”
政府部门和机构在将近两年的时间里，在两个政府之下使用了Google的4000亿英镑的数字。 自2025年11月(在本周入学前将近一年)以来，部长们的估计数一直较低，然而负责学徒工作的政府机构英格兰技能公司(Speech England)仍在四个月后公布旧数字。
Nayaran的议会回答是WIRED能够找到的第一批记录证据，说明政府将两个数字并列，或者说报告是由Google委托的。 答案并没有撤回4000亿英镑的数字，也没有说这是错误的。
担任公共科学、创新和技术委员会主席的劳工议员Dame Chi Onwurah告诉WIRED:“政府应该促进AI等技术的潜力，以改善公共服务。 然而，这些报告突出说明了实现公共服务数字化转型的一个中心障碍，即杂音。
“经济项目不可避免地依赖假设，但过分强调技术的好处有可能损害变革的理由。 政府必须实事求是地看待AI这样的技术能够提供什么，并且向公众公开潜在的节约。”
全球促进论坛强调，自上而下更多地采用人工智能，并将其纳入公务员工作流程，作为如何改进利用的实例。 “尽管我们还没有改变我们对于技术总体潜力的看法，但鉴于我们在实践中所看到的采用速度较慢，我们对到2030年可能实现的潜力的中央估计要接近政府的数目——之后的几年内增长加快了。
2025年1月，保守派同行Richmond的Holmes勋爵向部长们询问了4000亿英镑索赔的起源，但没有得到答复。 他告诉WIRED:“不幸的是，政府一再使用的数字，然后，毫不奇怪，其他多个组织现在已经作了重大和正确的调整。 政府若能尽早更直接地澄清此事
他补充说：“ 罗布斯特数据至关重要，至少是数十亿磅我们的钱，以及政府如何选择部署它取决于它。 ”
超过1200亿英镑，前科技部长彼得·凯尔在宣传AI的好处的同时也使用了4000亿英镑，而政府以外的许多议员融资质疑围绕该技术的潜在问题。
政府关于AI能为经济增加多少的订正概算是受欢迎的，但他们是在近两年的部长引用Google支付的研究数字后提出的，“这反映出更广泛的格局。 看上去准确的AI数字往往含有假设和激励因素，业界往往资助或塑造背后的研究。
“政府在制定政策之前，应先测试所给出的数字，为独立研究提供资金，并衡量承诺的收益是否兑现。 它应该总是首先提出简单的问题，然后使用AI带来的经济或生产力增益的任何数字——它来自何处，它假设什么，谁从某个数字中实际受益？”
与内阁办公室、政府中负责大赦国际的部门以及Google进行了接触，征求意见。
PF Global 称继续为Google工作，但所有研究都是独立的，所有判断和假设都是自己的。
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For the last two years, the UK government has been telling the British public that the country could receive an economic boost of £400 billion, thanks to AI, a figure intended to calm fears that the technology would lead to sweeping job losses and even an economic crash.
But the UK AI minister admitted last week that figure was significantly higher than the government’s actual projections after it was revealed that assessment came solely from a report commissioned by Google, and that its own estimation of AI’s economic benefit was less than a third of that £400 billion figure.n
AI minister Kanishka Narayan, answering a parliamentary question on the issue, said that AI adoption and data investment could add £55 billion to £140 billion to the UK economy by 2030, bringing the central estimate to £120 billion. But even this “more recent assessment,” he said, was a “hugely uncertain” estimate.
Narayan said the £400b figure “was drawn from a publicly available 2023 report commissioned by Google and produced by Public First,” a British consultancy firm now referred to as PF Global.
Responding to WIRED’s questions about the difference between the figures, PF Global’s head of economics, Jonathan Dupont, said the disparity was partially because of what they saw as the government’s slow adoption of AI. “AI is a very fast moving technology, and, as we learn more, we inevitably have to update the assumptions lying behind our models. Compared to our older model, the numbers the government uses assume a much slower rate of adoption than looked possible back in our model that was created in 2023.”
Government departments and agencies used Google’s £400 billion figure for almost two years, under two governments. Ministers have had the lower estimate since at least November 2025, almost a year before this week’s admission, yet Skills England, a government agency responsible for apprenticeships, was still publishing the old figure four months later.
Nayaran’s parliamentary answer is the first recorded evidence WIRED could find of the government setting the two numbers side by side, or saying that the report was commissioned by Google. The answer did not withdraw the £400 billion figure or say it had been wrong.
Dame Chi Onwurah, the Labour MP who chairs the Commons Science, Innovation and Technology Committee, told WIRED: “The government is right to promote the potential for technology like AI to improve public services. However, these reports highlight one of the central barriers to delivering the digital transformation of public services my committee has identified: hype.
“Economic projects inevitably rely on assumptions, but overstating the benefits of technology risks undermining the case for change. The government needs to be realistic about what technology like AI can deliver and be transparent with the public about potential savings.”
PF Global highlighted more top-down adoption of AI and integration into civil service workflows as examples of how take-up could improve. “While we haven’t changed our view on the overall potential of technology, given the slower rate of adoption we’ve seen in practice, our central estimate for the amount of potential likely to be achieved by 2030 is much closer to the Government’s number—with growth ramping up in the next few years after that.”
Lord Holmes of Richmond, the Conservative peer who asked ministers in January 2025 about the origins of the £400 billion claim but did not receive a response, told WIRED: “It is unfortunate that the figure used repeatedly by the government, and then, unsurprisingly, by multiple other organizations has now been significantly and rightly adjusted. It would have been better for the government to clarify this much sooner and more directly.”
He added: “Robust data is critical, not least as billions of pounds of our money and how the government chooses to deploy it depend on it.”
The spat over these two numbers—£120 billion and £400 billion—is part of a wider debate over the line between government support and boosterism. Former technology minister Peter Kyle also used the £400 billion while promoting the benefits of AI, while many parliamentarians outside of government raised questions about potential issues around the technology.
“The government’s revised estimates for how much AI could add to the economy are welcome—but it’s concerning that they come after almost two years of ministers citing a figure from research that was paid for by Google,” Sumedha Deshmukh of the Ada Lovelace Institute told WIRED. “This reflects a wider pattern. Figures about AI that look precise often have assumptions and incentives built into them, and industry often funds or shapes the research behind them.
“The government should test the numbers it is given before it builds policy on them, fund independent research, and measure whether promised gains are delivered. It should always start by asking simple questions before it uses any number around economic or productivity gains from AI—where did it come from, what does it assume, and who actually benefits from a given figure?”
The Cabinet Office, the department responsible for AI in government and Google, were approached for comment.
PF Global said their work for Google continued but all research was independent and all judgments and assumptions were their own.
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