AI Spending is Slowing Down. How Will the S&P 500 React?

Wall Street keeps setting records, yet a growing chorus of institutional voices now names artificial intelligence (AI) itself as the biggest threat facing global markets.

The S&P 500 sits at the center of that argument, and its concentration explains why.

S&P 500 Index (SPX) – All-Time Performance. Source: TradingView

Why Fund Managers Now Fear AI Most

A tail risk is a low-probability event with severe consequences, the kind fund managers watch even when markets look calm. AI just claimed the top spot on that list.

Bank of America’s July Global Fund Manager Survey found 45% of respondents naming an AI bubble as the biggest tail risk, up from 28% the previous month.

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Wall Street’s New Top Fear: The AI Bubble Displaces Inflation in BofA’s Fund Manager Survey. Source: BofA via Hedge Fund Tips

That figure displaced second-wave inflation from its first-place position. The same survey identified long positions in global semiconductors as the world’s most crowded trade.

Respondents also flagged a specific trigger. Hyperscaler spending on AI infrastructure is ranked as the most likely source of a credit event.

Analyst Mac10 sharpened the warning on August 8. He argued that forward earnings growth is accelerating at a record pace only because companies are pouring unprecedented cash into artificial intelligence.

S&P 500 forward earnings estimates are growing at the fastest rate in history, as record balance sheet capital gets thrown down the shit hole of AI, where it flows throw the P&L as a ONE TIME event. Record corporate stock and bond issuance now ensure that AI itself is the… pic.twitter.com/fOf5cwihMi

— Mac10 (@SuburbanDrone) August 8, 2026

His concern centers on accounting mechanics. That spending often appears as a one-time boost on profit statements rather than sustainable operating performance.

Institutional bodies echo those doubts. The Bank for International Settlements warned earlier this year that Big Tech’s spending spree risks becoming a prolonged investment bust. The numbers behind that alert are substantial. The five largest hyperscalers are expected to deploy more than $1 trillion across 2025 and 2026.

Household exposure raises the stakes further. Ordinary investors now hold more stocks relative to their wealth than in past cycles, so any sharp drop would hit harder than the dot-com crash.

What the S&P 500 Actually Reveals

The structural problem explains why the index matters. J.P. Morgan Global Research estimates that the top 20 stocks now account for roughly 50.8% of total market capitalization.

That concentration has no modern precedent. Half a century has passed since the index depended so heavily on so few companies. The practical implication is uncomfortable. Buying the market increasingly means buying the AI trade, regardless of how the remaining 480 companies perform.

Cumulative Weight of S&P 500 Companies. Source: Slickcharts

Capital commitments keep expanding regardless. Goldman Sachs estimates annualized AI-related spending could exceed $800 billion by the end of 2026.

Morgan Stanley projects even larger flows. Its research points toward nearly $3 trillion of AI infrastructure investment by 2028, with over 80% still ahead.

Summer has already delivered a stress test. The Nasdaq fell almost 10% from its June peak by late July before staging a near-9% rebound in early August to a new all-time high, according to TradingView data.

Momentum names showed particular fragility. Sandisk and Western Digital, up roughly 396% and 145% year-to-date, both displayed sell-the-news vulnerability during earnings season.

Sandisk (SNDK) Price Performance – YTD. Source: TradingView

The bull case rests on delivered results, however. Goldman Sachs found 64% of reporting S&P 500 companies beat consensus earnings by at least a standard deviation.

BlackRock rejects the bubble framing outright. Today’s leaders generate real profits, maintain strong balance sheets, and largely fund investments from their own cash flow.

Extraordinary earnings are buying time for the AI trade. Whether returns eventually justify trillions in capital expenditure remains the question holding up the entire index.

The Situational Awareness Collapse: A Warning Shot for the AI Trade

If markets needed a case study of AI concentration risk, July delivered one. Situational Awareness, the hedge fund founded by former OpenAI researcher Leopold Aschenbrenner, grew to as much as $45 billion before steep losses on AI infrastructure stocks like SK Hynix forced it to sell its entire public portfolio to Ken Griffin’s Citadel.

The timing was brutal: on July 24, Aschenbrenner had sent investors a letter reporting a 439% net return for the first half of 2026 — even suggesting it was a good time to add funds.

One hedge fund turned a 225% winner into a 40% loss in a single month, and it may have marked the low.A long/short momentum trade inside US tech returned 225% in the year to June, then shed nearly 40% in July as Situational Awareness, Leopold Aschenbrenner's AI fund, imploded… pic.twitter.com/0EljZeuCbb

— Kurt S. Altrichter, CRPS® (@kurtsaltrichter) August 7, 2026

Six days later, Citadel absorbed a stake once estimated at $16 billion in one of the largest rushed equity transactions in Wall Street history. A cascade of margin calls shrank the fund’s assets from $45 billion to roughly $10 billion in a matter of weeks.

Yet the story did not end there. Just days after the near-collapse, Aschenbrenner returned to the market with a $400 million investment in a privately held company — bringing his combined commitment to that unnamed target to $500 million, alongside the fund’s retained private stakes.

The episode does not prove the AI trade is over, but it exposes how concentration, leverage, and thin liquidity can destroy a portfolio before a long-term thesis has time to play out — the same fragility now embedded, at index scale, in the S&P 500 itself.

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