Apple’s new AI leader is Amar Subramanya, whose formal title is vice president of AI. He reports to software chief Craig Federighi and leads work on Apple Foundation Models, machine-learning research, AI safety, and evaluation. The appointment is part of a wider reorganization—not a simple one-for-one replacement of former AI chief John Giannandrea—and its real test is whether Apple can turn its AI plans into reliable features users can actually access.
What changed in Apple’s AI leadership?
Apple announced Subramanya’s appointment on December 1, 2025. The company calls him its vice president of AI; “AI chief” is a convenient shorthand, not his formal title. He reports to Craig Federighi, Apple’s senior vice president of Software Engineering, rather than directly to CEO Tim Cook. Apple assigned Subramanya responsibility for Apple Foundation Models, machine-learning research, AI safety, and evaluation. Apple’s announcement said his expertise would contribute to the company’s ongoing innovation and future Apple Intelligence features.
The change also reshaped where AI work sits. Some of Giannandrea’s former responsibilities shifted toward Federighi, services chief Eddy Cue, and operations chief Sabih Khan. That makes this both a leadership succession and an organizational change: Apple is distributing AI responsibilities across software, services, and operations rather than putting every function under one executive.
Who is Amar Subramanya?
Subramanya previously served as corporate vice president of AI at Microsoft. Before that, he spent 16 years at Google, where he was head of engineering for Google’s Gemini Assistant. That experience spans AI research and the work of incorporating models into consumer products, a combination relevant to Apple’s effort to make Siri more capable.
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His background is a reason the appointment may matter, not evidence that Apple’s products will improve. The outcome will depend on execution: model quality, integration into operating systems and apps, safety, and the ability to deliver features on schedule.
What happened to John Giannandrea?
Giannandrea joined Apple in 2018 and was senior vice president for Machine Learning and AI Strategy. Apple said he would step down, remain as an adviser, and retire in spring 2026. His former organization included Apple Foundation Models, Search and Knowledge, machine-learning research, and AI infrastructure.
Subramanya took over important AI responsibilities, but Apple did not give him Giannandrea’s former title or leave the former organization intact. The company’s announcement describes a redistribution of responsibilities as well as a new appointment. It does not establish that Giannandrea was fired or that he alone was responsible for Siri’s delays.
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Why did Apple reorganize its AI work?
Apple said the leadership changes were intended to strengthen its AI work and accelerate future Apple Intelligence features. It also said Federighi had been instrumental in developing a more personalized Siri. Those are the company’s stated rationale; they do not prove that the new structure will deliver better products.
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Why Siri is the central test
Apple’s AI leadership change came after delays to more ambitious personalized Siri features. That timing makes Siri a natural measure of the reorganization, but Apple has not said Subramanya was hired solely to fix a failed Siri project.
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At WWDC on June 8, 2026, Apple previewed a substantially expanded Siri AI. Apple described features including understanding personal context, recognizing onscreen content, answering questions using broader web knowledge, and taking actions across apps and system experiences. It also announced a dedicated Siri app with conversation history and expanded visual and multimodal capabilities. These are announced capabilities, not independent test results or proof of general availability. Apple’s Siri AI announcement said developer testing would begin through its developer program and that a consumer beta was planned for later in 2026.
Those milestones are different: a developer test is not a public beta, and neither is the same as a finished general release. Whether Siri can reliably find relevant information in messages, email, and photos, understand what is on screen, and complete tasks—not just describe them—will matter more than the preview.
What Apple Intelligence’s architecture means
Foundation models are the underlying AI models used to power features. Apple’s next-generation Apple Intelligence combines on-device processing with Private Cloud Compute: Apple says core experiences can run on a device, while more complex requests can use servers built with Apple silicon. The arrangement reflects a basic trade-off: local processing can reduce reliance on a server, while more demanding tasks may require cloud computing.
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Apple says Private Cloud Compute does not store user data and uses it only to fulfill requests. Those are Apple’s stated privacy commitments, not a guarantee that should be treated as an independent security audit. Apple’s Apple Intelligence overview explains the company’s architecture, while its Siri and Apple Intelligence page describes the consumer-facing system.
For Subramanya’s remit, model development is only one part of the work. Evaluation and safety help determine whether models behave reliably; product integration determines whether users can invoke them in useful ways; and privacy architecture shapes which tasks can run locally or in the cloud. Some server-dependent features, including image generation, may have daily usage limits. Apple says most iCloud+ plans provide increased access to some of those features; the announcement does not make iCloud+ a general requirement for Apple Intelligence.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which devices and users may get the new features?
Compatibility depends on both hardware and software, and access to a compatible device does not mean every feature is available immediately. For its next software generation, Apple listed these supported device groups for Apple Intelligence and Siri AI:
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- 6.7inch Super Retina XDR display. ProMotion technology. Always-On display. Titanium with textured matte glass back. Action button
- Dynamic Island. A magical way to interact with iPhone. A17 Pro chip with 6-core GPU
- Pro camera system. 48MP Main | Ultra Wide| Telephoto. Super-high-resolution photos (24MP and 48MP). Next-generation portraits with Focus and Depth Control. Up to 10x optical zoom range
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- iPhone 16 models and later, plus iPhone 15 Pro and iPhone 15 Pro Max.
- iPad mini with A17 Pro, and iPads with M1 or later.
- MacBook Neo with A18 Pro, and Macs with M1 or later.
- Apple Vision Pro.
- Apple Watch Series 9 or later and Apple Watch Ultra 2 or later; Apple Watch SE 3 when paired with an Apple Intelligence-enabled iPhone nearby.
Apple’s current compatibility information also lists newer models, including iPhone 17 devices and iPhone 16e. The software generation Apple named for the upcoming features is iOS 27, iPadOS 27, macOS 27, watchOS 27, and visionOS 27. Hardware eligibility, operating-system version, feature rollout, and regional availability are separate conditions.
Language and regional availability
Apple said the Siri AI beta would initially be for supported devices set to English, with more languages planned. Apple Intelligence supports a broader set of languages, including English, Danish, Dutch, French, German, Italian, Norwegian, Portuguese, Spanish, Swedish, Turkish, Vietnamese, simplified and traditional Chinese, Japanese, and Korean; individual features may still vary by language and region.
Apple said Siri AI would not initially be available on iPhone, iPad, and Apple Watch in the European Union. Mac and Apple Vision Pro users in the EU could access it when their devices are set to a supported language. The new Apple Intelligence features would also not initially be available in China while Apple works through regulatory requirements. These limits mean a device that qualifies on paper may not offer the same feature set everywhere.
How to tell whether the appointment worked
A leadership change is not a product result. The useful scorecard is what Apple ships and how it performs:
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- Delivery: Does Siri AI move from developer testing to the promised beta and then to general availability? Do features arrive consistently across supported devices?
- Reliability: Can Siri retrieve relevant personal context, understand onscreen material, and complete actions accurately?
- Privacy: Are the on-device and Private Cloud Compute practices clearly documented, and can outside researchers meaningfully assess the security model?
- Model and product quality: How does Siri compare with assistants such as Gemini and ChatGPT on accuracy, reasoning, multimodal understanding, and task completion?
- Developer usefulness: Can third-party apps use Apple’s AI capabilities through practical integrations and permissions?
- Access: How much do hardware, language, and regional restrictions limit who can use the features?
These tests also expose the main risks. A distributed leadership structure may improve coordination with software and services while making ownership harder to track. Cloud processing can enable more complex tasks while introducing connectivity needs and usage limits. Hardware requirements can leave owners of older devices out. And a polished preview can raise expectations that a beta or final product may not meet.
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