J.P. Morgan sees a pile of red flags in the AI market

Jun 27, 2026

J.P. Morgan warns that "there are signs of investor exuberance" in AI-related financial markets.

Since ChatGPT launched in 2022, just 42 AI companies in the S&P 500 have driven roughly 65 to 80 percent of the entire index's profits, revenues, and investments, according to J.P. Morgan.

The semiconductor rally is showing technical patterns that look a lot like the dotcom bubble. Hedge funds are heavily invested in chip and hardware stocks, margin lending on the Korean stock exchange is climbing, and retail traders are piling into semiconductor options.

Leveraged chip ETFs, funds that amplify price swings, have quintupled their influence on global stock markets since early 2024. Only a handful of stocks are carrying the gains.

Stock market gains are concentrated in a few companies

J.P. Morgan also warns about extreme concentration. The ten largest US stocks now account for about 40 percent of the S&P 500's market cap. In 2015, that figure was 17 percent.

The bank puts the concentration numbers in a global context, though. Despite the increase, the US still ranks among the markets with relatively low stock market concentration. Only India and Japan are less concentrated.

Nvidia still holds the biggest share of the AI accelerator market, the specialized chips used for AI workloads, but that share is slipping from 85 percent in 2023 to an estimated 75 percent by 2026, according to J.P. Morgan.

Custom chips from major cloud providers like Google's TPUs or Amazon's Trainium cut operating costs by 30 to 40 percent compared to Nvidia GPUs. Anthropic, for example, has committed to running its AI Claude on Amazon's Trainium for the next decade.

China is squeezing margins

J.P. Morgan also flags familiar risks around revenue at leading AI labs like OpenAI and Anthropic. Their sales are growing fast, but compute costs are massive, and future profitability remains unclear.

Rising token prices could push companies to switch to cheaper open-source models. There are already signs of this. Companies are shifting tasks to cheaper models, average token prices are falling, and Chinese open-source models are approaching top-tier performance at a fraction of the cost.

Tech investment's share of economic growth is also rising, while free cash flow margins at major cloud providers are shrinking and their debt financing is growing.

All told, J.P. Morgan says AI is creating multiple layers of concentration risk across markets, infrastructure, and the broader economy. NYU finance professor Aswath Damodaran has warned the same thing, saying an AI crash could hit harder than the dotcom bust.