The Bank of England’s governor has warned finance ministers and central bankers from the world’s largest economies that the rapid spread of artificial intelligence carries the risk of tipping the global economy into a downturn, according to a report in the Guardian.
The intervention, delivered to the G20, marks one of the starkest assessments yet from a senior central banker about the macroeconomic consequences of the AI boom. It reframes a technology usually discussed in terms of productivity gains and growth potential as a possible source of instability â one that policymakers may be poorly equipped to manage.
Why central bankers are worried
Central bankers have been circling the AI question for some time, and their concerns tend to fall into two broad categories.
The first is financial. Enormous sums have flowed into AI companies, chipmakers and the data centres needed to train and run large models. That investment has become a significant driver of stock market gains and, in some economies, of capital spending and construction activity. If expectations about future AI profits prove too optimistic, a sharp repricing of those assets could hit household wealth, corporate balance sheets and bank lending â the classic transmission channels through which a market shock becomes a recession. Concentration is part of the problem: when a handful of firms account for an outsized share of index values, a fall in their valuations is felt across pension funds and passive investment portfolios worldwide.
The second concern is about the labour market and the real economy. If AI systems displace workers faster than new roles emerge, the result could be a period of weak demand, with rising unemployment in white-collar and service occupations that have historically been relatively insulated from automation. Economists disagree sharply about the likely pace and scale of that adjustment, which is precisely what makes it difficult for policymakers to plan for.
A hard problem for policy
AI presents an unusually awkward challenge for monetary authorities. A genuine productivity boom would tend to lower inflation and raise potential growth, arguing for looser policy. A speculative bubble that bursts would demand a different response entirely. Distinguishing between the two in real time is close to impossible â a dilemma familiar to anyone who has studied the late 1990s technology boom and its aftermath.
Regulators also face questions about AI’s use inside the financial system itself. As trading desks, insurers and lenders adopt similar models and data sources, there is a risk of herding behaviour that amplifies market moves, alongside more prosaic operational risks such as heavy reliance on a small number of cloud and chip suppliers.
What the G20 can do
The G20 has no power to slow the development of AI, and few of its members would want to. Its role is more modest: coordinating monitoring, agreeing on how exposures should be measured and disclosed, and stress-testing banks and non-bank financial institutions against scenarios in which AI-linked assets fall steeply.
Raising the alarm at a forum such as the G20 is, in that sense, part of the job. Central bankers are expected to identify tail risks well before they materialise, and warnings of this kind are not predictions. The Bank of England’s message appears to be less that a downturn is coming than that governments should not assume the AI story can only end well â and should prepare for the possibility that it does not. Read More
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