JPMorgan Warns AI Stock Split Echoes 1990s Tech Bubble Patterns

The Divergence Between Infrastructure and Hyperscalers

A growing rift has emerged within the AI-driven bull market. Infrastructure suppliers such as chipmakers continue to rally, while hyperscale cloud computing giants that have heavily invested in AI are stalling. This pattern of “shovel sellers”—chipmakers and infrastructure providers—benefiting, while the “shovel buyers”—tech giants making large-scale purchases of AI computing power—are being penalized by investors, has become the dominant theme of the year. This divergence is characterized by strong semiconductor stocks and weak cloud mega-cap companies.

The scale of this spending is immense. Four major hyperscalers—Meta, Microsoft, Amazon, and Alphabet—are projected to spend a combined $725 billion on AI-related capital expenditures in 2026. JPMorgan separately estimated that five major hyperscalers would collectively spend around $697 billion. Despite these massive outlays, investor sentiment toward these tech giants has cooled. MarketWatch reports that the Roundhill Magnificent Seven ETF (MAGS) is up about 1.5% year-to-date, a stark contrast to the PHLX Semiconductor Index (SOX), which has risen by more than 70% over the same period. In early July 2026, the Philadelphia Semiconductor Index had surged 87% year-to-date. Meanwhile, Meta is down 5% and Microsoft is down 18% over the same period, with Microsoft posting its worst monthly loss since the year 2000 in June.

JPMorgan’s 1990s Bubble Comparison

JPMorgan strategist Jason Hunter’s note draws a pointed comparison to the late 1990s, when hardware and infrastructure companies ran hot while the companies spending on that infrastructure started wobbling. Hunter warned clients on Wednesday that if hyperscale cloud computing giants fail to break through key technical resistance levels, while semiconductor stocks remain stuck below their own critical resistance, the rotation within AI-related stocks could escalate into a broader market correction. Hunter urged market participants to pay close attention to individual hyperscaler performance charts over the summer months. The thesis is straightforward: if Meta, Microsoft, Amazon, and Alphabet can stabilize and show signs of recovery before autumn, the broader market probably holds together.

Quantitative Alerts and the Mid-August Window

Beyond technical charts, JPMorgan is monitoring its quantitative team’s AI Bubble Sentiment Score, which tracks how intensely AI bubbles are discussed in global media. The score peaked on June 29 and is now declining. However, the absolute score remains at 687, which is within the top five percent of historical levels. Even if cooling begins now, as long as it stays in this high range, there is still a 53.8% probability that the SOX will experience a pullback of more than 8% over the next 20 days. Historically, such narrative cycles take about 1.5 months to shift from hot to cold, with the lowest point expected as early as mid-August. The Philadelphia Semiconductor Index (SOX) has fallen approximately 19% since hitting its all-time high on June 22, nearing the 20% threshold for a bear market. JPMorgan’s quantitative model is clear: the AI alert has not been lifted, and buying AI semiconductors before mid-August carries high risk.

Sector Context and Future Outlook

While JPMorgan remains cautious, other firms have offered different perspectives. Morgan Stanley offered a slightly more optimistic read in early July 2026, suggesting that a sector rotation from semiconductor momentum toward hyperscalers might already be underway. Meanwhile, the broader ecosystem continues to expand. At the 8th Future Investment Initiative conference, Elon Musk predicted that by 2040 there would be at least 10 billion humanoid robots. According to Musk, this technology could be worth $250 trillion by 2040. Major firms like PwC and McKinsey still see AI unlocking multi-trillion-dollar potential, even as current earnings results from Alphabet and Tesla arrived this week to a chilly reception as both boosted artificial-intelligence spending plans amid continued investor fretting over the potential payoff.

Sources: Marketwatch.