Markets are Missing This: Apple Stock Offers a Different Way to Bet on the Future of AI

The sharp rally in AI chipmakers is beginning to lose momentum. Investors are questioning whether hyperscalers can make returns that justify their massive investments, with some quietly preparing for a slowdown in the nearly $1 trillion AI spending cycle.

According to UBS estimates, hyperscalers' capex will rise 76% this year to $673 billion, but will increase by only 25% next year and just 6% in 2028. Though these entities have initially funded the AI buildout through their own cash, hyperscalers are now turning to external financing which raises huge questions on capital-market pressures and spending growth.

Lower-cost competition from China is adding another layer of uncertainty to the AI investment landscape. In latest news, Beijing-based startup Moonshot AI has launched Kimi K3, a 2.8-trillion-parameter model that claims to close the gap with leading U.S. offerings and even surpasses OpenAI and Anthropic's most capable systems on some benchmarks.

Kimi K3's release is a testament to the possibility of increasingly capable AI models made available at substantially cheaper prices in the future. This will eventually weaken the pricing power of those selling proprietary AI services.

Morgan Stanley analyst Gary Yu views the release of Kimi K3 as an all-round catch-up of LLMs:

"K3 has received positive feedback globally, signaling an all-round catch-up of Chinese LLMs with US leaders in model size, performance, and pricing. K3, the largest open-weight Chinese LLM so far, may suggest the scaling law still holds... We do not view K3 as an overnight miracle but rather as the result of cumulative progress across China's AI model industry."

If AI becomes cheaper, companies may begin to use lower-cost models for routine tasks and save the advanced ones for complex work. However, if this happens, model developers and cloud providers may find it harder to generate attractive returns on their costly infrastructure investments.

This is what makes Apple Inc. (NASDAQ: AAPL ) an interesting contrast, relying more on on-device AI and less on massive data center spending. This contrast particularly became evident on July 17, with Apple briefly unseating Nvidia and becoming the world's most valuable company. Reclaiming the top spot since the first time since April of last year, Apple's s move to the top was a reflection of how investors are reassessing their outlook of artificial intelligence.

"Apple was seen as a laggard in the AI race because it wasn't spending to develop models, but now sentiment has changed," said Toni Meadows, head of investment at BRI Wealth Management.

"Apple is less exposed to capex intensity and better positioned to monetize AI via services, ecosystem lock-in, and hardware upgrades. The re-rating reflects confidence in earnings durability rather than speculative AI upside."

Previously known to be an AI laggard, Wall Street now believes Apple's AI agenda and light capital spending model will eventually make it an AI star. HSBC recently upgraded the stock to a buy rating, citing its AI capabilities and innovative pipeline.

"This AI boost comes at the right moment, when we think Apple has one of its most innovative product pipelines in place," they wrote.

It's true, analysts are now praising Apple Inc. (NASDAQ:AAPL) for its wait-and-see strategy, letting the rivals take on the task of research and development along the way. The company's latest iOS public beta gives regular users the opportunity to try its redesigned, large-language model powered Siri.

Even though Siri's core architecture and standalone application are Apple developments, Apple has also formed strategic partnerships with AI leaders such as Google and OpenAI, integrating their Large Language Models (LLMs) into Apple's ecosystem for advanced generative AI features.

This way, Apple's AI strategy of side-stepping the capital-intensity trap facing hyperscalers may turn out to be a huge win. The company relies on cloud partners for the most compute-intensive workloads, while also retaining control of its consumers. Meanwhile, its AI features support Services revenue and strengthen eco-system lock-in.

Turning to the bull case, cheaper AI shifts value away from whoever owns the most expensive model to the one who controls distribution. This means Apple can use AI to sell more devices and services across its enormous established base without having to spend massively on infrastructure. The company already boasts an installed base with more than 2.5 billion active devices, a testament to "incredible customer satisfaction for the very best products and services in the world."

The bear case, however, centers on valuation friction. At nearly $330 per share, the stock trades at roughly 38 times expected fiscal 2026 earnings, which is well above its historical average in the mid-20s. Apple trades at a premium multiple that assumes it can sustain steady earnings growth despite the mature nature of its hardware replacement cycle. This could become a risk if consumers see little reason to upgrade their iPhones for AI features, particularly in cases where open-source models run smoothly on browsers or old devices. In such a case, Apple's premium valuation may be harder to justify.