Apple has officially entered the generative AI race with Apple Intelligence. But the timing, the delivery, and the approach raise real questions about how far behind they are – and whether their privacy-first, edge-computing strategy is enough to catch up.
Here’s a deep dive into where things stand: delays, internal issues, partnerships, and why rivals like OpenAI are pulling ahead fast.
Apple’s Delayed Launch: What’s Really Happening?
Apple announced Apple Intelligence in mid-2024, well after Microsoft, Google, and OpenAI had already released mature tools. And the rollout has been rocky:
Key features are delayed: On-screen context awareness, deeper Siri integration, and in-app actions are all postponed. Some features may not arrive until 2026 (FT).
Hardware limitations: Only the latest devices (iPhone 15 Pro, M-series iPads and Macs) support Apple Intelligence, shrinking the user base out of the gate.
Core experiences aren’t ready: Siri’s long-promised overhaul isn’t shipping this year, and several AI-driven features are either experimental or limited.
This puts Apple in the awkward position of having announced an AI push – without the capabilities to back it up yet.
Internal Turmoil: AIML Problems at Apple
Apple’s internal AI/ML division has reportedly been disorganised and unfocused:
Frequent leadership changes and shifting goals have created friction.
Staff reportedly referred to the group as “AIMLess”, reflecting the lack of clear direction (Futurism).
Siri has failed to evolve, despite years of internal efforts and pressure from execs like Craig Federighi to push things forward.
All of this has slowed down Apple’s ability to innovate in the generative space – especially compared to Microsoft’s tight integration of Copilot across Windows and Office, or Google’s continuous Gemini updates.
Apple’s Strategy: Edge AI, On-Device Models, and Privacy
Apple isn’t trying to compete with ChatGPT or Claude in raw model performance. Their AI vision focuses on:
Running smaller models directly on devices with Apple silicon.
Minimising cloud usage, only invoking secure Apple Private Cloud Compute when needed.
Avoiding large-scale data collection, sticking to their privacy-first approach.
This plays to their strengths – hardware control, chip optimisation, and privacy reputation – but it also limits what they can do in terms of generative creativity, scale, and real-time learning.
You won’t find anything close to GPT-4 on an iPhone. What you’ll get instead is tightly scoped AI features that summarise your emails, rewrite text in Notes, or clean up images – all with minimal user control.
The ChatGPT Integration: A Smart Shortcut
Knowing their own models weren’t ready, Apple turned to OpenAI. The partnership gives Siri the ability to:
Route advanced queries to GPT-4 (with user consent).
Let users access ChatGPT for writing, editing, and Q&A in Mail, Safari, and Notes.
Support both free and paid ChatGPT accounts for deeper functionality.
This move was pragmatic. Apple gets access to a leading LLM without having to build one from scratch. But it also highlights a gap – Apple doesn’t yet have a foundational model that can rival Claude, Gemini, or GPT-4.
Meanwhile, OpenAI Keeps Building – Fast
While Apple is catching up, OpenAI is accelerating. The latest move: OpenAI is in talks to acquire Windsurf (formerly Codeium), a fast-growing AI-powered code editor, for around $3 billion.
Why it matters:
Strengthens OpenAI’s developer tools and positions them to compete with GitHub Copilot more directly.
Shows they’re doubling down on productisation, not just core models.
Suggests a long-term plan to own not just the LLM layer, but the full dev tooling ecosystem.
Compare this to Apple, who currently has no AI developer tools, APIs, or open ecosystem around Apple Intelligence.
Market Response: Not Great
Early indicators suggest that Apple’s cautious rollout is having an impact:
iPhone sales dropped 13% in China, and global growth was flat during the holiday season when AI features were first promoted (AP).
Apple’s news summarisation feature had to be pulled after it produced inaccurate and misleading summaries.
Developer reaction has been muted – partly because Apple Intelligence is closed off and not accessible via SDKs or APIs.
For a company that normally sets trends, Apple’s AI launch feels reactive, not leading.
Final Word: Apple’s in the Race, But Struggling to Keep Pace
Apple was the last major tech player to announce generative AI products. And while they’ve taken a privacy-first, edge-based approach, it’s becoming clear they’re struggling to stay relevant in the current AI landscape.
They don’t have their own leading model.
Their flagship assistant, Siri, remains underdeveloped.
Their ecosystem is closed and limited.
By contrast, companies like OpenAI and Microsoft are expanding aggressively – into code, search, productivity, developer platforms, and more.
If Apple wants to avoid falling even further behind, they’ll need to do more than refine Notes summaries and grammar suggestions. They’ll need to show they can lead in AI – not just implement it as a footnote to the iOS experience.
Until then, they’re in the race – but they’re not setting the pace.
