For equities, UBS’s view supports semiconductor and hardware names into an earnings season where results, rather than narrative, are expected to drive the AI trade. The near-term test arrives quickly, with ASML reporting on Wednesday and the major cloud providers later in the month, and any shortfall against the accelerating cloud growth UBS expects would likely hit richly valued megacaps hardest. Rates add a second risk: a hot US inflation print on Wednesday that lifts Treasury yields would weigh on long-duration tech valuations regardless of fundamentals. UBS’s preference for quality and defensive tech reflects that risk of sharp swings even within a supportive backdrop.
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UBS still sees the AI boom running on real demand, but after nearly five years it wants investors to be pickier about where they ride it.
Summary:
- UBS says recent industry data continue to point to robust demand for AI compute and infrastructure
- Meta’s Muse AI assistant has recorded more than 6.6 million downloads and 1.8 million daily active users in its first month, according to Sensor Tower data
- TSMC reported a 51% rise in quarterly revenue, Samsung flagged an almost ninefold jump in operating profit, Hon Hai beat sales estimates and Marvell raised its fiscal 2028 revenue forecast
- UBS expects average hyperscaler cloud revenue growth of 58% in the September quarter, up from 48% in the June quarter
- The bank warns concerns over growth, financing and safety could cause bouts of volatility
- It recommends a diversified approach favouring quality chip and hardware names, megacap platforms and defensive tech
Demand for artificial intelligence remains robust and fundamentals are likely to drive the AI trade through the coming earnings season, according to UBS, which pointed to strong chipmaker results and early signs of consumer appetite for AI agents.
The bank highlighted Meta’s Muse AI assistant, which has recorded more than 6.6 million downloads and 1.8 million daily active users since its launch a month ago, according to data from Sensor Tower. AI agents are tools that can carry out tasks on a user’s behalf rather than simply answering questions. UBS said it was too early to judge uptake of other recently launched agents, but described the early numbers as an encouraging sign that wider adoption could add further to AI demand.
Semiconductor results point the same way. TSMC reported a 51% rise in quarterly revenue, while Samsung flagged an almost ninefold jump in quarterly operating profit ahead of its full results. AI server assembler Hon Hai Precision Industry beat sales estimates, and chip designer Marvell raised its fiscal 2028 revenue forecast. UBS expects third-quarter earnings to provide further evidence of strong demand for AI compute and infrastructure.
Monetisation by the hyperscalers, the largest cloud computing providers, will be a key focus. UBS expects their average cloud revenue growth to accelerate to 58% year on year in the September quarter from 48% in the June quarter. It sees consumer AI agents as a potential next growth driver, opening revenue streams from subscriptions, advertising and transactions, and argues broader adoption would lift cloud utilisation, creating a clearer link between heavy infrastructure spending and revenue.
UBS acknowledged the risks. As the AI trade approaches its fifth year, it said concerns over growth, financing and safety could continue to trigger periods of volatility. It advised investors to stay engaged with what it sees as a structural opportunity while becoming more selective, favouring a diversified approach built around high-quality semiconductor and hardware beneficiaries of AI spending, megacap platforms and defensive technology companies.
The view will be tested quickly, with ASML reporting on Wednesday and the major cloud providers due later in the month.
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Key terms explained
AI agents: Software that can carry out tasks on a user’s behalf, such as booking, buying or organising, rather than simply answering questions like a chatbot. Because they act as well as respond, they open up new ways for companies to earn money, from subscriptions to commissions on transactions.
Hyperscalers: The handful of giant technology companies that run the world’s largest cloud computing networks and rent out computing power and storage to businesses. They are the biggest buyers of AI chips and data centre equipment, so their spending and results are a key barometer for the whole AI trade.
AI compute: The raw processing power needed to train and run AI models, supplied mainly by specialised chips in large data centres. Rising demand for compute is what drives orders for chipmakers and server builders.
Monetisation: How companies turn AI investment into revenue. Investors have questioned whether the enormous sums spent on data centres will pay off, so evidence of AI-related sales growth is closely watched each earnings season.
Cloud utilisation: How much of a cloud provider’s installed capacity is actually being used and paid for. Higher utilisation means data centre spending is generating revenue rather than sitting idle.
AI server assembler: A manufacturer that builds the complete computer systems housing AI chips, combining processors, memory, cooling and networking into racks for data centres. Hon Hai, also known as Foxconn, is the largest.
Megacap platforms: The very largest listed technology companies, each worth well over a trillion dollars, whose products reach billions of users and give them scale to profit from AI.
Defensive tech: Technology companies with steadier, less cyclical earnings, such as established software or services firms, that tend to hold up better when markets turn volatile.
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What is hyperscaler cloud growth?
The companies: Hyperscalers are the handful of technology giants that run the world’s largest cloud computing networks, chiefly Amazon Web Services, Microsoft Azure and Google Cloud. They rent computing power, storage and AI tools to businesses over the internet, so customers don’t need to build their own data centres.
What the growth figure measures: Hyperscaler cloud growth is the year-on-year increase in revenue from these cloud businesses. Analysts often average it across the main providers to gauge how fast demand for cloud services, and increasingly AI services, is expanding.
Why it matters for AI: The hyperscalers are spending tens of billions of dollars a year on data centres and AI chips. Their cloud revenue growth is the clearest sign of whether that spending is paying off. Faster growth suggests customers are actually using and paying for AI capacity; slowing growth would raise questions about overbuilding.
Why markets watch it: Because the hyperscalers are the biggest buyers of AI chips and servers, their cloud results ripple through the entire AI supply chain, from chipmakers such as TSMC to server builders such as Hon Hai.
Where it stands: UBS expects average hyperscaler cloud revenue growth to accelerate to 58% year on year in the September quarter, up from 48% in the June quarter. The figures will be tested when the major cloud providers report later this month.
“The most advanced AI on the planet and the desk head tells me to go fetch his dry cleaning.”
This article was written by Eamonn Sheridan at investinglive.com.