While Big Tech rivals race to spend billions of dollars on AI infrastructure, Apple appears to be taking a different route. It is using its available computing capacity only where needed and directing the maximum resources towards product development, software integration, and user experience.
The spending gap is stark! Apple spent about $6.8 billion over nine months, while Amazon, Alphabet and Meta each shelled out $30–54 billion in just one quarter. Collectively, hyperscalers are expected to spend $600–725 billion this year.
Why is Apple avoiding the AI race?
The strategy appears to be a deliberate decision by Apple to avoid competing head-on in the expensive race to build the largest AI infrastructure. But it also raises a bigger question – can Apple really sustain growth without matching its rivals’ aggressive AI spending?
“Apple’s approach seems less focused on competing with big AI companies and more on using AI to strengthen its ecosystem,” said Kumar Rajagopalan, Vice President, Strategic Initiatives and Country Head India at Dexian.
Obviously, it has its advantages, Rajagopalan said, such as its large customer base and tightly integrated hardware-and-software ecosystem. Instead of trying to control every layer of AI technology, the company can afford to leverage existing computing resources while focusing its spending on product development, custom silicon, software, privacy, and user experience.
Can Apple really afford to ignore AI?
That does not mean Apple can simply ignore AI. As and when AI becomes an everyday part of consumers’ lives, the company will have to convince customers that its products remain advanced and useful.
“It surely seems possible for Apple to grow its business without focusing on AI, but sometimes doing without AI can be complicated,” Rajagopalan said.
Apple’s R&D spending shows that it is still investing heavily in innovation. The company spent about $34.5 billion on R&D in fiscal 2025, covering custom silicon, software, services, AI, health technologies and new product categories.
The key difference between Apple and other hyperscalers is that “Apple may be looking beyond the LLM race and towards a world where AI is embedded into the products people already use,” said Atul Rai, CEO and Co-Founder of Staqu Technologies.
Apple’s reported acquisition of Q.ai, which works on machine learning for audio, could offer another clue. Rather than building another large language model, the technology focuses on areas such as helping devices understand whispered speech and operate in difficult acoustic environments.
“This suggests that Apple may be thinking about AI across multiple modalities and device experiences—audio, vision, wearables and on-device intelligence—rather than treating AI as synonymous with LLMs,” Rai said.
So, can this strategy deliver sustainable growth?
Industry experts believe it can—provided Apple uses AI effectively rather than simply spending more on computing power.
“We believe significant investment in AI infrastructure will remain necessary, particularly for companies developing large foundation models. But we don’t think every company needs to follow exactly the same path,” Rai said.
For Apple, the long-term bet could therefore be less about owning the biggest AI model and more about putting useful intelligence into the devices it already sells.
“The AI race may not ultimately be about who owns the most compute, but who uses intelligence most effectively,” Rai said.