Apple covered a lot of ground Thursday when it announced record Q1 results, but perhaps what mattered most were the insights into how the company now thinks about artificial intelligence, Siri, and Google Gemini.

Apple’s forthcoming, existentially significant and much smarter Siri will be powered by Apple’s collaboration with Google Gemini and the company told us a little about how it will work: it will work on-device or use Apple’s Private Cloud Compute (PCC) system. (Apple also confirmed PCC servers are already being manufactured and shipped from a US factory.)

Private, integrated, relevant

“These AI experiences are personal, private, integrated across our platforms, and relevant to what our users do every day,” said Apple CEO Tim Cook.

The hybrid approach reflects Apple’s decision to broaden its AI capabilities by partnering with Google. For a fee, the company will help Apple by providing frontier model capacity, though Cook and company remain in command of execution — including where the AI calculations take place and ensuring privacy. 

You can easily see this as a rejection of the hyperscaler dependency visible across the entire industry, one that means future Apple Intelligence tools will work on the device nearly all the time, or in the cloud on highly secure server systems otherwise. In the future, will users even need to outsource requests to other firms, or will the combined tech do everything they need?

We don’t yet know.

What we do know

But what we do know is that this approach to AI deployment should be water in the desert to enterprises in regulated industries, who will need things like auditability, data minimization and jurisdiction control. 

It won’t be a perfect answer – many will still seek self-hosted AI, sovereign data solutions, and tightly constrained service selection. A second consideration might be that processors for Private Cloud Compute are manufactured in the US, which suggests defense-adjacent, infrastructure, and public sector entities will look positively at Apple’s solutions during future buying cycles.

Apple cited two deployment stories that show us the road to come:

• Astra Zeneca: The company has deployed 5,000 M5-powered iPad Pros across its pharmaceutical sales team to take advantage of AI capabilities, including Apple Intelligence.
• Snowflake: The move to standardize around Mac has led to a reduction in support costs. (The Mac deployment story is significant in the quarter, with platform shipments far surpassing the industry average, confirming the switch from Windows is intensifying, worldwide.)

Supported by its Google Gemini partnership, Apple will now be able to build and deploy additional Apple Intelligence features to help people get things done more efficiently. “We believe that we can unlock a lot of experiences and innovate in a key way through the collaboration,” said Cook.

Apple’s customers are ready for private AI

With that in mind, it is also important to reflect on Apple’s admission that the majority of users on enabled iPhones are actively using Apple Intelligence. This bodes well, as those features scale across its now 2.5 billion customers.

To expand on this initial adoption, Apple only needs to build a deeper catalog of AI features, which it is now working on with Google.

Will it attempt to monetize its AI features? That’s a tough call. Apple refused to say, suggesting it sees its approach as a platform-enabling tech, probably to the detriment of some, not all, the third-party AI services elsewhere available.

For enterprise purchasers, this also means Apple products now compete as platforms for AI-enabled workflow acceleration. That’s a new arrow for the company bow, one that joins other enterprise-focused competitive edges in its quiver, including TCO, power/performance, employee choice, and endpoint security.  

But challenges remain

It is not unusual that Apple’s management spelled out a super-optimistic vision of what’s coming next in AI, but significant challenges remain, and not just the dangers of political upheaval, tariffs, and the impact of war on the company supply chain.

When it comes to hardware, two of the most significant challenges include memory and processor manufacture. The first problem could affect Apple’s margins, somewhat, but the challenge most likely to put a brake on the company’s continued market expansion is perhaps more profound: Apple confirmed iPhone supply is currently constrained by processor availability. 

“To be specific, it’s the advanced nodes like 3-nanometer where our latest SoCs are produced that are gating the Q2 supply,” Cook said. “We are currently constrained, and at this point, it’s difficult to predict when supply and demand will balance.”

With Apple Silicon inside every Apple device at this point, the inference here is clear: Demand for Apple products has grown so high it can’t make them fast enough. While that’s a good problem to have, it might also contribute to Apple’s purported decision to split the iPhone release cadence into two significant launch windows, since doing so might help manage immediate demand for this precious component.

It might also form a kind of warning to enterprise purchasers planning large-scale Apple deployments, as it suggests those orders could take longer than usual to fulfill. Though it seems certain at this point that reports of Apple’s demise in AI may have been overexaggerated.

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