AI Chips Have Powered Most S&P 500 Gains
The S&P 500's rally over the last two years has been driven by a narrow group of AI-focused giants. Through May 22, 2026, the broad index is up about 41%, a level reached largely on the backs of a handful of AI-enabled leaders rather than broad-based earnings across the market.
Prominent AI chipmakers and their ecosystem partners have delivered outsized gains. NVIDIA has logged roughly a 102% rise in value over the period, while AMD has surged about 181%. Both names remain deeply valued by investors, trading at elevated multiples as the market bets on continued AI adoption and supply-chain momentum.
What makes this market phenomenon notable is the degree to which this subset of stocks has steered the overall index. A market note referenced in the analysis shows that if you strip AI infrastructure and AI-related component stocks from the S&P 500, the two-year return falls to roughly 16%, a stark contrast to the reported 41%.
- SPY two-year return through May 22, 2026: 41%
- NVIDIA (NVDA) two-year return: ~102%
- AMD (AMD) two-year return: ~181%
- Return without AI infrastructure exposure: ~16%
- Gaps in performance: ~26 percentage points between the full index and the AI-excluded subset
- Macro backdrop: 10-year yields around 5%; VIX below its 12-month average; consumer sentiment near recessionary levels
- Valuations: NVIDIA trades ~33x trailing earnings; AMD sits around 156x forward P/E
Taken together, these data points underscore a market where a few AI megacaps drive most gains, while the rest of the market lags behind. The concentration has sparked debate about whether the S&P 500 is truly representative of the broader economy or simply a rolling bet on AI-enabled growth.
The Math That Should Terrify Index Investors
Many market observers frame the situation in stark terms: the math that should terrify index investors. When a small group of AI-adjacent stocks account for a disproportionate share of gains, passive exposure becomes an implicit bet on a single trend rather than a diversified strategy.
“This is not just a stock-picking problem; it’s a concentration problem embedded in the math of passive investing,” said Dr. Elena Park, senior market strategist at Horizon Research. “If you removed the AI infrastructure group from the S&P, the performance gap tells you all you need to know about the market’s current structure.”
The implications extend beyond performance metrics. The current environment also features a 5% yield on the 10-year Treasury, sentiment flares that hint at recession risks, and a VIX that sits below the long-term average. In other words, the market is priced to endure continued AI-driven strength even as broader economic signals cool off.
Market veterans caution that the math behind these gains may not hold if AI demand softens, supply chains shift, or regulatory curbs emerge. The risk is not merely a correction in a handful of names, but a potential reweighting of risk across portfolios designed to ride broad indices rather than pick winners.
What This Means for Passive and Active Investors
For passive investors, the recent data is a reminder that index performance can hinge on a few mega-cap names. The risk is twofold: concentration risk in the index itself and the possibility of a regime change that favors other sectors or stock types once AI hype cools.
Active managers, meanwhile, see an opportunity to question whether high-flying AI names deserve their premium as the rest of the market remains comparatively muted. Some fund managers are weighing more balanced exposure to traditional consumer, financials, and industrial bets to reduce single-theme risk.
Portfolio construction in this environment may require a blend of tactics, including selective hedging, regional diversification, and a sober assessment of valuation discipline. The overarching message: if the math that should terrify index investors is valid, investors may want to stress-test their risk tolerance against a potential AI downturn or abrupt shifts in regulatory or supply-chain dynamics.
What to Watch Next
As markets continue to digest AI-related growth, several factors could reshape the math behind index performance in the coming quarters:
- Regulatory developments around AI chips, data privacy, and export controls that could alter demand or margins
- Inflation and macro data that could push the 10-year yield higher or lower, affecting valuations
- Corporate earnings resilience in non-AI sectors to determine how broad-based the next leg of market gains can be
- Technological breakthroughs or supply constraints that re-run the AI-capital cycle’s math
Investors should consider whether their portfolios adequately reflect a scenario in which AI exposure loses momentum or reverses, and how that would affect long-term returns. In a market that looks less forgiving as the AI boom matures, the math that should terrify may become a practical issue for retirement plans and long-term goals.
Bottom Line
The past two years have shown a market that can be skewed by a few AI megacaps, lifting the S&P 500 while leaving broad-based performance more muted. The 26-point gap between the AI-driven gains and the rest of the index is a striking visual of concentration risk that could redefine how investors view passive versus active strategies.
As of May 2026, the data support a sobering takeaway: the math that should terrify index investors is not just a theoretical concern. It is a real-world signal that portfolio diversification and risk management should be as much a part of the conversation as growth targets and stock-picking bets. For now, the AI-chips-led rally remains a powerful force, but its staying power may hinge on a complex mix of demand, supply, and policy that could alter the market's trajectory in the months ahead.
Discussion