Apple is finally shipping. After 18 months of broken promises—beginning with its June 2024 announcement of Apple Intelligence—the company will unveil a genuinely functional Siri in February powered by Google's Gemini. This isn't hype. According to Mark Gurman at Bloomberg, this version will actually complete tasks by accessing your personal data and screen content—the very promises Apple made 18+ months ago. The inflection point is stark: Apple stopped building AI and started borrowing it. That's not failure. That's pragmatism at scale.

The clock on Apple's AI ambitions just restarted. After spending 18 months between its June 2024 Apple Intelligence announcement and now delivering essentially nothing that worked, the company has made a bet that matters: use Google's Gemini instead of proprietary models. This isn't a retreat. This is an inflection. And it changes what's possible for enterprise AI in consumer products.

Here's what's actually happening. Apple will announce a new Siri in the second half of February, according to Gurman's reporting. This version uses Gemini and, crucially, can finally do what Apple promised 18 months ago: complete actual tasks by reading your personal data and what's on your screen. Not asking you for clarification. Not needing API integrations you set up yourself. Real task completion from a voice assistant that understands context.

Then comes June. At WWDC, Apple plans an even bigger reveal—a version of Siri that's genuinely conversational, built more like ChatGPT, and potentially running directly on Google's cloud infrastructure. That last detail matters more than it initially appears. Apple has decided that for the cutting-edge conversational experience, it's better to route requests to Google's servers than run everything locally or on-device.

Why does this matter now? Because the entire industry has been watching whether large language models could actually integrate into mainstream consumer interfaces without breaking the user experience. Apple had 18 months to prove it could happen with its own models. It couldn't. The evidence is brutal: constant delays, the departure of AI chief John Giannandrea, and internal reports that the company's AI roadmap was "bullshit," according to Apple's own Mike Rockwell, as Gurman reported. That's not spin. That's institutional acknowledgment that the strategy failed.

So Apple pivoted. Instead of building foundation models from scratch, it's leveraging Google's—which means using a proven, production-ready system rather than experimenting with building blocks. For Microsoft, which solved this by integrating OpenAI's models into Office and Windows, this validates the hybrid approach. For Amazon and Meta, which are still primarily betting on proprietary approaches, this is a competitive signal worth watching.

The February timing is critical. That announcement comes before the next wave of iPhone 18 OS updates, giving Apple a chance to ship functional AI before competitors' next flagship releases. If Siri actually works—if it completes tasks without hallucinating or failing to understand context—then the bar for assistant intelligence just moved higher across the industry. Builders will immediately begin asking whether they need to integrate Gemini too. Enterprise decision-makers will see a template: AI features matter, but borrowed intelligence beats broken homegrown attempts.

The June announcement at WWDC is where Apple signals direction to developers. Running conversational Siri on Google's infrastructure is a choice that tells developers: your apps will increasingly offload complex reasoning to cloud models, and Apple's providing the layer that makes it natural. That's a platform shift wrapped in a product feature.

What's being tested here isn't whether AI works. It's whether embedding third-party LLMs into existing consumer products can feel seamless and reliable. Apple's 18-month failure proved the inverse—trying to proprietary-solution your way to AI capability doesn't work at consumer scale. Google's partnership gives Apple a way to win the next inflection: proving that AI-first interfaces can be both powerful and predictable.

The window for assistant transformation opens in February. For builders, this means the reference implementation for LLM-integrated assistants shifts from proprietary models to hybrid cloud approaches—Gemini powering consumer interfaces changes what you should architect. Investors should watch February execution validation: if Siri actually works, this proves enterprise AI can embed at scale. Enterprise decision-makers have a timeline now: February shows whether AI-powered assistants are ready for deployment decisions, June confirms the conversational bar. Monitor February's actual capability delivery—not the promises, but what it actually does—for your next 12-month strategy.