[AI]Why Apple chose Google over OpenAI: What enterprise AI buyers can learn from the Gemini deal

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Apple’s 

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 to integrate

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’s Gemini models into its revamped Siri marks more than just another Big Tech partnership. The deal, announced Monday, offers a rare window into how one of the world’s most selective technology companies evaluates foundation models—and the criteria should matter to any enterprise weighing similar decisions.

The stakes were considerable. Apple had been publicly integrating ChatGPT into its devices since late 2024, giving OpenAI prominent positioning within the Apple Intelligence ecosystem. 

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’s Gemini win represents a decisive shift in Apple’s AI infrastructure strategy, one that relegates OpenAI to what Parth Talsania, CEO of Equisights Research, describes as “a more supporting role, with ChatGPT remaining positioned for complex, opt-in queries rather than the default intelligence layer.”

The evaluation that mattered

Apple’s reasoning was notably specific. “After careful evaluation, Apple determined

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’s AI technology provides the most capable foundation for Apple Foundation Models,” according to the joint statement. The phrasing matters—Apple didn’t cite partnership convenience, pricing, or ecosystem compatibility. The company explicitly framed this as a capabilities assessment.

For enterprise buyers navigating their own foundation model selections, this carries weight. Apple’s evaluation criteria likely mirrored concerns familiar to any organisation building AI into core products: model performance at scale, inference latency, multimodal capabilities, and crucially, the ability to run models both on-device and in cloud environments while maintaining privacy standards.

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’s technology already powers Samsung’s Galaxy AI across millions of devices, providing proven deployment evidence at consumer scale. But Apple’s decision unlocks something different: integration across more than two billion active devices, with the technical demands that come with Apple’s performance and privacy requirements.

What has changed since ChatGPT integration

The timing raises questions. Apple rolled out ChatGPT integration just over a year ago, positioning Siri to tap into the chatbot for complex queries. The company now states, “there were no major changes to the ChatGPT integration at the time,” but the competitive dynamics have clearly shifted.

OpenAI’s response to

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’s Gemini 3 release in late 2025—what reports described as a “code red” to accelerate development—suggests the competitive pressure was real. For enterprises, this highlights a risk often underweighted in vendor selection: the pace of model capability advancement varies significantly between providers, and today’s leader may not maintain that position across a multi-year deployment.

Apple’s choice of a multi-year agreement with

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, rather than maintaining flexibility to switch between providers, suggests confidence in

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’s development trajectory. That’s a bet on sustained R&D investment, continued model improvements, and infrastructure scaling—the same factors enterprise buyers need to assess beyond current benchmarks.

The infrastructure question

The deal raises immediate concerns about concentration. “This seems like an unreasonable concentration of power for

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, given that they also have Android and Chrome,” Tesla CEO Elon Musk 

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 on X. The critique isn’t just competitive positioning from xAI’s founder—it reflects a legitimate enterprise concern about vendor dependency.

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now powers AI features across both major mobile operating systems through different mechanisms: directly via Android, and through this partnership for iOS. For enterprises deploying AI capabilities, the parallel is clear: relying on a single foundation model provider creates technical and commercial dependencies that extend beyond the immediate integration.

This makes Apple’s architectural approach worth examining. The company emphasised that “Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple’s industry-leading privacy standards.” 

The hybrid deployment model—on-device processing for privacy-sensitive operations, cloud-based models for complex tasks—offers one template for enterprises balancing capability with data governance requirements.

Market implications beyond mobile

The deal’s immediate impact was measurable: Alphabet’s market valuation crossed US$4 trillion on Monday, with the stock having jumped 65% in 2024 on growing investor confidence in its AI efforts. But the strategic implications extend beyond market caps.

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has been methodically building positions across the AI stack—frontier models, image and video generation, and now default integration into iOS devices. For enterprises, this vertical integration matters when evaluating cloud AI services: a provider’s foundation model capabilities increasingly connect to their broader infrastructure, tools, and ecosystem positioning.

Apple’s setbacks on the AI front—delayed Siri upgrades, executive changes, lukewarm reception for initial generative AI tools—are instructive from another angle. Even companies with enormous resources and talent can struggle with AI product execution. The decision to partner with

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rather than persist with entirely proprietary development acknowledges the complexity and resource demands of frontier model development.

The search revenue connection

The Gemini deal builds on an existing commercial relationship that generates tens of billions in annual revenue for Apple:

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pays to remain the default search engine on Apple devices. That arrangement has faced regulatory scrutiny, but it establishes precedent for deep technical integration between the companies.

For enterprises, this underscores how commercial partnerships in AI often extend beyond pure technology licensing. The search deal likely influenced negotiations around the Gemini integration, just as existing vendor relationships shape enterprise AI procurement. Those relationships can be advantages—established trust, proven integration capabilities—or constraints that limit evaluation of alternatives.

The OpenAI question

The deal leaves OpenAI in an awkward position. ChatGPT remains available on Apple devices, but as an optional feature rather than the infrastructure layer. For a company that has positioned itself as the AI leader, losing default integration to

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represents a strategic setback.

For enterprises, this competitive dynamic offers a reminder: the foundation model market remains fluid. Provider positioning can shift quickly, and exclusive relationships between major players can reshape options for everyone else. Maintaining optionality—through abstraction layers, multi-model strategies, or portable architectures—becomes more valuable in rapidly evolving markets.

What comes next

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stated that Gemini models will power not just the revamped Siri coming later this year, but “other future Apple Intelligence features.” The scope of integration will likely expand as Apple builds out its AI capabilities, creating deeper technical dependencies and raising the stakes of the partnership.

The financial terms remain undisclosed, leaving an important variable opaque: how did Apple and

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structure pricing for this scale of deployment? Enterprise buyers negotiating foundation model licensing will be watching for any signals about how such deals get priced at a massive scale.

Apple’s decision doesn’t make

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’s Gemini the obvious choice for every enterprise—far from it. But the deal does offer validated evidence of what one extremely selective technology company prioritised when evaluating foundation models under demanding requirements. For enterprise AI buyers navigating their own evaluations, that’s a signal worth considering amid the noise of vendor marketing and benchmark leaderboards.

The question isn’t whether to choose what Apple chose, but whether your evaluation criteria are as rigorous as Apple’s appears to have been.

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