Apple Turns to Google’s Gemini AI for Siri: What It Signals About AI Strategy, Risk, and Control
If 2025 wasn’t the year of cyber threats, then it was almost certainly the year of AI (could we have called it twenty twenty fAIve there? Sorry, we promise that’s the last one..).
AI is perhaps one of the most polarising things out there. Sure, there’s no doubting the efficiency on day-to-day tasks, such as brainstorming, helping organise daily tasks, aiding decision-making, or revamping security. But to some, the resources it uses are a concern (to say the least); others point out that it infringes on the artistic space, replacing the soulful and human aspect of imagery or video, to the dismay of most, and lacks creativity and harms those in these industries, to put it mildly.
Despite all that, and whether you think AI is a bubble (see also: NFTs), it hasn’t stopped some of the big names from entering and then fully committing to it, with the likes of OpenAI, Google, Claude, and the controversial Grok being among the most prominent players out there. Yet, one big name has been, perhaps surprisingly, absent, choosing instead to watch from the wings. And this week’s news may be a sign that they’re not about to dive into AI just yet.
We’re talking, of course, about Apple, which has confirmed a multi-year partnership with Google, under which Google’s advanced Gemini artificial intelligence models will power the next generation of Siri, Apple's voice assistant, and broader Apple Intelligence features later in 2026. This represents a strategic shift for Apple, which has historically developed its core technologies in-house, but has seemed to be a step behind others in the AI space. These new capabilities are expected to roll out with iOS 26.4, signalling a deeper integration of third-party AI into Apple’s ecosystem.
A Strategic Move in a Fast-Moving AI Landscape
Apple’s decision is significant, and it’s not because they lack expertise. We all know they have robust machine-learning teams, but the pace of AI innovation has made independent development increasingly challenging. Training and maintaining large-scale AI models with performance that meets user expectations requires immense computational resources, specialised talent, and data infrastructure.
By partnering with Google’s Gemini models, Apple accelerates the delivery of AI-enhanced features without waiting for in-house systems to catch up to, or even reach the same capability level as, where we are at this minute in time, in early January 2026. It doesn’t seem like all that long ago where we had those hideous, nightmare-fuelled AI videos of Will Smith eating spaghetti to show how bad generations are. These days, it’s so far ahead that it’s frightening, for a multitude of reasons that have been well-documented.
This shift itself highlights a broader trend, though: even the largest tech companies are open to strategic collaboration when it delivers a competitive edge. If you needed further proof, Google is already the default search engine on Safari for iPhones.
At the same time, this decision enhances Google’s position in the AI ecosystem. Google’s AI infrastructure will power features on potentially billions of devices, extending the reach of Gemini beyond Google’s own products.
Is AI a Bubble, or a Consolidation Phase?
Moves like this inevitably reignite the question of whether artificial intelligence is a bubble. In reality, Apple’s decision suggests the opposite. Rather than downing tools or retreating from AI, it reflects a market entering a consolidation phase.
As AI capabilities mature, the cost and complexity of building competitive foundation models continue to rise. That creates natural gravity towards a smaller number of providers with the scale, infrastructure, and talent required to sustain them. For many organisations, including the largest technology companies, it no longer makes sense to own every layer of the stack.
This isn’t the bursting of a bubble; it’s the transition from experimentation to embedded infrastructure, where AI becomes a dependency to be governed rather than a novelty to be explored.
Privacy and Control Remain Central
Privacy has long been a core pillar of Apple’s brand. In announcing the partnership, Apple emphasised that Google’s AI will operate through Apple-controlled infrastructure, including on-device processing and Apple’s Private Cloud Compute, rather than sending user data directly into Google’s systems.
This distinction matters.
Apple aims to integrate advanced AI while maintaining its privacy posture. However, integrating a competitor’s AI underneath user-facing services creates a new kind of dependency, and it’s one that organisations should watch closely as they build their own AI strategies.
Three Key Themes for Organisations
1. Strategic AI Partnerships Are Becoming Normal
Apple’s decision shows that collaboration between competitors in AI is not unusual. Speed of innovation matters, and companies will leverage partnerships where it accelerates the delivery of capabilities. For organisations adopting AI, this underscores a broader lesson: sometimes the optimal path to capability is not building everything yourself, but integrating best-in-class models through partnerships.
This doesn’t mean ceding control. It means aligning governance, compliance, and integration strategies with business priorities early on.
2. Dependency Risk Cannot Be Ignored
Strategic partnerships accelerate innovation but create dependencies. When core capabilities such as AI inference and large-model execution live outside your organisation, factors like vendor roadmap changes, cost, data policies, and availability become risk vectors that need active management.
Organisations should be clear about where dependencies lie in their AI stacks and build controls and exit strategies accordingly.
3. Governance, Data Protection, and AI Compliance Are Now Board Issues
AI is no longer a developer-only concern. Decisions about which AI models to integrate, how data flows through them, and what governance frameworks apply now sit at the intersection of security, legal, and strategic leadership.
Apple has chosen to embed Google’s AI while reinforcing privacy commitments. Organisations should similarly design AI governance that balances innovation speed with compliance and risk management, especially where third-party providers are involved.
A Broader Lesson for AI Adoption
Apple’s partnership with Google marks a shift in how major technology companies are approaching artificial intelligence. It underscores a broader reality in the AI ecosystem: collaboration and competition often coexist. Even organisations known for internal capability development are prepared to integrate external expertise when it advances their strategic goals.
For organisations of all sizes, this is a reminder to think about AI strategy holistically. Owning every component of your AI stack is no longer the only path to innovation. What matters now is aligning capability with governance, understanding where risk resides, and governing dependencies with the same discipline applied to core infrastructure risk.
The Last Word
Apple’s decision to integrate Google’s Gemini AI to power Siri and Apple Intelligence illustrates how fast the AI landscape is evolving, and how traditional models of in-house development are giving way to hybrid strategies that combine internal control with external capability.
For organisations evaluating AI adoption, the imperative is clear. Build your strategy with both innovation and risk in mind. Strategic partnerships can accelerate capability, but they also demand governance, monitoring, and a clear understanding of dependency risk. This balance will increasingly define how effectively organisations leverage AI while protecting their systems, data, and stakeholders.