A privacy-first company licensing intelligence from an advertising giant signals a deeper shift in how the industry will build, deploy, and finance the next generation of digital assistants
Apple is paying Google about 1B dollars per year to power the next version of Siri.
That alone captures how unusual this moment is.
A company built on privacy and control is now licensing intelligence from the world’s largest advertising company.
Bloomberg’s report was clear.
Apple Intelligence slipped behind schedule.
Siri could not deliver reliable multi-step actions.
Several promised iPhone 16 features never reached users.
Inside Apple, the strain was obvious and top engineers left.
At the same time, the market signaled something important.
Most users are not upgrading their phones for AI features.
The figure sits around 10 to 11 percent.
People still care more about battery life, cameras, stability, durability, and performance.
Chinese manufacturers moved with that insight.
Xiaomi, Honor, Vivo, and others doubled down on fundamentals.
Large batteries.
Silicon carbide charging.
Better thermals and even liquid cooling.
Efficient open-source models running directly on the device.
These improvements are felt every day.
So Apple faced a practical decision.
Delay another product cycle, or secure a reliable reasoning engine fast.
Licensing Gemini became the simplest way to ship a working assistant while maintaining control.
This part matters.
Gemini does not run on Google servers.
It runs inside Apple’s Private Cloud Compute environment, using Apple hardware and Apple isolation.
Google never sees the data.
Privacy stays in place while capability is delivered.
There is also a long-standing financial symmetry here.
Google pays Apple close to 20B dollars a year to stay the default search engine.
Apple now pays a smaller amount in return for reasoning capability.
Both sides get strategic value.
The larger question is what this means for the future of AI infrastructure.
If Apple can rent the intelligence it needs, then replace it later with its own model, the industry may need to rethink the enormous spending on training and scaling every model internally.
Open-source models continue to improve.
On-device intelligence is getting stronger.
Users reward practical reliability more than parameter counts.
This suggests that the real advantage may shift away from owning the biggest model toward owning the execution layer.
The layer that turns user intent into real action.
Apple is renting today.
Once its own model reaches the required level, it can switch away from Gemini without the user noticing.
The interface stays familiar.
The ecosystem remains Apple’s.
The economics shift back to Cupertino.
The Apple and Google deal is more than a short-term patch.
It is a preview of how intelligence may be delivered going forward: modular, interchangeable, and optimized for integration rather than brute force.
The full analysis is in the video above.
Would love to hear your perspective on what this means for the future of AI spending and platform strategy.