Inside the new Siri AI and the privacy paradox of Apple Intelligence

Apple's new Siri can run your digital life. The catch is privacy.

To run errands across apps, Apple’s upgraded assistant needs deep access to personal data the company has walled off for years

During Monday’s keynote at Apple’s Worldwide Developers Conference (WWDC), a presenter asked Siri to plan a watch party for a World Cup match. The virtual assistant pulled the tournament schedule from the Internet, dug through the user’s Messages history to find a mention of coconut cookies, drafted an invitation featuring the recipe, and prepared to send it to a group chat. Siri carried out this choreography without the user ever touching an app.

The proactive assistant Apple has promised—and repeatedly delayed—for two years has, it seems, finally arrived . But to pull off this kind of digital errand-running, Siri needs deep access to personal data Apple has spent years walling off: your mail, photos, messages and calendar. Each new capability expands the territory the company’s privacy architecture must cover. At WWDC, Apple’s keynote speakers kept returning to the same privacy claims: user requests to Siri stay private, data is not retained after processing, and outside researchers can inspect the system.

Florian Schaub, who studies usable privacy at the University of Michigan, says Apple’s openness to outside scrutiny is welcome—but limited. “Consumers often lack the expertise to inspect code,” he says, but by publishing specifications and letting researchers and regulators examine its systems, Apple “at least facilitates external validation of their claims.”

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The new Siri relies on an architecture Apple calls the System Orchestrator, a layer that coordinates data flowing among Spotlight’s Semantic Index, onscreen information and an App Toolbox that carries out actions inside apps. Siri’s underlying reasoning rests on a new generation of Apple Foundation Models , including a top-tier cloud model the company calls AFM Cloud Pro, which is custom-built for Apple hardware and refined from Google’s Gemini frontier AI models. When a request is too complex for a phone, Apple says Private Cloud Compute handles it on servers that do not retain user data and can be inspected by outside researchers. The largest of these models was reportedly derived from a specialized version of Gemini with about 1.2 trillion parameters, according to Bloomberg , which Google has licensed to Apple for about $1 billion a year. Ahead of Monday’s keynote, The Information reported that some of that cloud processing might run on Nvidia chips inside Google’s data centers.

Apple executives have distinguished the deployment from Google’s consumer AI stack and model-serving infrastructure. Yet until Apple opens this hybrid cloud arrangement to the outside inspection it invites for Private Cloud Compute, the data-routing security of these models rests largely on the company’s word.