Earnings momentum is broadening beyond large-cap tech

• The earnings backdrop is broadening. Expectations are improving not just in US mega-cap technology, but also in smaller companies, value shares and emerging markets.
  
  
• AI’s effects are spreading through the economy. Benefits are showing up across semiconductors, data-centre infrastructure and sectors involved in building, powering and cooling that infrastructure.
  
  
• Market leadership could widen. If AI investment continues and its benefits spread more broadly, the earnings picture for global equities may become less concentrated in a handful of large technology stocks.

Corporate earnings expectations are rising, even compared with the generally rosy view from the last quarter or two. The direction appears clearly higher over the next couple of years, driven by areas beyond US growth and the Magnificent Seven.

The pace of earnings growth is running measurably above that of the last few years. At the same time, momentum is broadening. This pattern of rising expected corporate earnings relative to the recent past is most pronounced in small-cap, value and emerging markets. The pickup is more muted among US growth and the Magnificent Seven.

This is evident in the widening gap between forecasted earnings-per-share growth for the next 12 months and actual earnings-per-share growth for the previous 12 months for both US and emerging market equities.

The gap between forecasted and trailing earnings has widened

Note: This chart shows the gap between forecast earnings-per-share growth for the next 12 months and actual earnings-per-share growth for the previous 12 months for the MSCI USA Index and the MSCI Emerging Markets Index.

Sources: Vanguard, based on data from Bloomberg, as of 11 May 2026.

The AI buildout cycle is a key trend driving this stronger and broader earnings momentum. The ever-increasing AI capital spending of hyperscalers – big technology companies that build and operate vast, AI‑optimised cloud infrastructure – is estimated at about $800 billion for the year. This outlay is already translating into consistently better‑than‑expected revenue for companies tied to the global AI infrastructure supply chain. Beneficiaries include companies in the lithography, foundry, memory and storage areas of semiconductor manufacturing.

Within that ecosystem, the focus has been shifting towards the greatest bottleneck: high-bandwidth memory chips, which are critical for inference‑heavy use cases and AI agents, where latency – the time that passes between an AI input and output – is especially important. The emphasis on high-bandwidth memory chips is translating into explosive earnings growth and rising expectations, alongside robust price performance, for firms such as Micron Technology and SanDisk in the US and South Korean companies SK Hynix and Samsung.

The effects are not confined to semiconductors, but also influence physical sectors involved in building, powering and cooling data centres, such as companies in the energy, utilities, industrials and materials sectors. AI’s knock-on effects are unlikely to stop there. Companies beyond the immediate AI infrastructure firms will benefit as AI spreads throughout the economy and productivity increases.

The evolution of current trends is likely to hinge on a few key questions:

• Will the AI infrastructure buildout continue to strengthen, supporting semiconductors and Korea- and Taiwan-related earnings?
  
  
• How effectively will AI hyperscalers, such as Amazon, Alphabet, Meta and Microsoft, monetise their AI spending?
  
  
• Will the early signs of AI’s benefits spread and begin boosting company earnings and profit margins across sectors using AI?

All three issues bear monitoring. They hold the key to shaping the earnings growth profile of the global equity market that has been, and will continue to be, shaped by AI.