UBS Securities expects profit growth for S&P 500 companies to decelerate in 2027 and 2028, and it says a disproportionate share of what remains will come from just three semiconductor companies tied to the artificial-intelligence boom: Nvidia, Micron, and Broadcom. According to the investment bank's research, those three chipmakers could account for roughly 45% of the index's total earnings gain in 2027.
The forecast puts hard numbers on a trend that has been building for more than a year: the AI infrastructure buildout is reshaping the earnings profile of the entire U.S. stock market, concentrating profit growth in a handful of companies that supply the chips and memory that power data centers.
What UBS is projecting
UBS estimates S&P 500 earnings per share will reach $430 in 2027 and $490 in 2028. That would represent continued growth, but at a slower pace than the rapid expansion seen in recent periods. The bank's analysts argue that the deceleration reflects two forces: investors are increasingly scrutinizing how much companies are spending on AI data centers and what returns those investments will generate, and higher bond yields are raising the bar for what counts as an attractive stock.
Earnings per share, or EPS, is a common measure of a company's profitability on a per-share basis. When analysts forecast index-level EPS, they are essentially adding up expectations for every company in the S&P 500. A slowdown in that growth rate does not mean profits are falling — it means they are rising more slowly than before.
Why three chipmakers matter so much
Nvidia designs the graphics processing units that have become the workhorse of AI training and inference. Broadcom supplies networking chips and custom silicon that help stitch together massive data-center clusters. Micron is one of the largest makers of memory and storage, including the high-bandwidth memory that AI accelerators require. Together, these three sit at the center of the physical supply chain for AI computing.
When a small group of companies drives a large share of an index's earnings growth, it creates what investors call concentration risk. The S&P 500 is weighted by market value, meaning the largest companies have the biggest influence on the index's performance. If AI-related spending slows more than expected, or if competition erodes margins at these chipmakers, the ripple effects on broad index funds could be significant.
This is not a new dynamic. Markets have periodically been dominated by a handful of companies — energy giants in the 1970s, technology and telecom firms in the late 1990s. What is different now is the scale and the speed at which AI-related capital expenditure has flowed into a narrow set of suppliers.
What it means for investors
For everyday investors, the UBS forecast is a reminder that broad-market index funds are not as diversified as they might appear. A fund that tracks the S&P 500 may hold hundreds of stocks, but its returns can hinge on the fortunes of a few mega-cap names. Investors who own such funds are, indirectly, making a sizable bet on the AI trade continuing to deliver.
The other takeaway is about expectations. When earnings growth is forecast to cool, stock prices often need a different kind of support — either faster revenue growth, cost cuts, or a willingness among investors to pay a higher multiple for each dollar of profit. UBS points to rising bond yields as a headwind on that front. When safe government bonds offer higher yields, the appeal of riskier assets like stocks can diminish, particularly for companies trading at rich valuations.
Investors will likely watch several things in the coming quarters: capital expenditure guidance from major cloud providers and AI-focused companies, memory pricing trends that affect Micron's margins, and any signs that AI adoption is translating into measurable revenue for the businesses buying all this hardware. The gap between spending on AI and returns from AI is the central question for the next phase of this market.
UBS's view is not a prediction of doom. It is a call for slower, more selective growth — and a warning that the market's AI winners may need to keep delivering to justify their outsized role in portfolios.
