BoE warns over risk of AI bubble in financial markets

(Sharecast News) - The Bank of England warned on Wednesday of the risk of an Artificial Intelligence bubble in financial markets. In its latest quarterly update, the BoE's Financial Policy Committee (FPC) said that on a number of measures, equity market valuations appear stretched, particularly for technology companies focused on AI.

"This, when combined with increasing concentration within market indices, leaves equity markets particularly exposed should expectations around the impact of AI become less optimistic," it said.

The Bank noted that equity market valuations have increased since the second quarter, to near all-time highs, driven partly by strong second-quarter earnings from US technology firms.

It pointed out that the price appreciation of the largest technology firms this year has increased the concentration within US equity indices to record levels.

"The market share of the top 5 members of the S&P 500, at close to 30%, was higher than at any point in the past 50 years," it said.

The Bank said equity valuations appeared stretched, particularly in backward-looking metrics in the US.

For example, the earnings yield implied by the cyclically-adjusted price-to-earnings (CAPE) ratio was close to the lowest level in 25 years, comparable to the peak of the dot com bubble.

"Forward-looking valuation metrics and compression in US equity risk premia also remained elevated relative to historical levels, with the S&P 500 at a one-year forward price-to-earnings ratio of 25 times, but remained below the levels reached during the dot com bubble," the BoE.

"Some technology companies were trading at valuation ratios which implied high future earnings growth, and concentrations within US equity indices meant that any AI-led price adjustment would have a high level of pass-through into the returns for investors exposed to the aggregate index."

The Committee said the outlook for valuations was uncertain, with both downside and upside risks.

"Downside factors included disappointing AI capability/adoption progress or increased competition, which could drive a re-evaluation of currently high expected future earnings," it said.

"Material bottlenecks to AI progress - from power, data, or commodity supply chains - as well as conceptual breakthroughs which change the anticipated AI infrastructure requirements for the development and utilisation of powerful AI models could also harm valuations, including for companies whose revenue expectations are derived from high levels of anticipated AI infrastructure investment."