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📺 Title: Why Apple Just Gave Up on AI
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Apple, long revered for its innovation and meticulous product execution, is facing one of its most public and embarrassing setbacks in recent memory: falling behind in artificial intelligence. Once confident that it could catch up on its own terms, Apple has now reportedly struck a deal with its longtime rival, Google, to license a custom version of the Gemini AI model to power Siri. This move—unthinkable just a year ago—marks a rare admission of failure for a company that prides itself on vertical integration and in-house engineering excellence.
But this story goes far beyond a single product delay. It raises fundamental questions about the value of AI in smartphones, the sustainability of the AI arms race, and whether companies like Apple even need to build their own large language models (LLMs). In this comprehensive guide, we’ll unpack every detail from internal chaos at Apple to consumer sentiment, technical shortcomings, strategic implications, and what this all means for the future of AI in consumer tech.
Apple’s Public Confidence vs. Private Reality
In December 2023, Apple executives Johnny Shroudy and John Turners dismissed concerns about Apple falling behind in AI, stating, “I don’t believe we are” and “Not too worried.” At the time, this seemed like typical Apple composure. But by early 2025, the truth had become undeniable.
According to internal reports, in March 2025, Robbie Walker, a senior director at Apple, described the delays in Apple Intelligence as “ugly and embarrassing” and called the decision to publicly promote unfinished AI features an “absolute disaster.” Despite being heavily advertised as the centerpiece of the iPhone 16—released over a year prior—these promised AI capabilities never materialized for users.
The $1 Billion Lifeline: Apple Turns to Google
Recent reporting from Bloomberg reveals that Apple is now in talks to pay Google $1 billion per year to use a custom version of its Gemini AI model to power Siri. This deal represents a dramatic reversal for a company that has historically avoided relying on competitors for core technologies.
Key details of the arrangement include:
- The custom Gemini model will reportedly have 1.2 trillion parameters, vastly outpacing Apple’s internal LLM, which stands at only 150 billion parameters.
- For privacy and security, the model will run on Apple-controlled private cloud infrastructure, not Google’s servers.
- Apple will likely remain silent about Google’s involvement in marketing materials to preserve its “privacy-first” brand image.
Why This Isn’t as Shocking as It Seems
Ironically, Apple already pays Google $18 billion annually to keep Google Search as the default search engine on iPhones. Spending $1 billion—just over 5% of that amount—for a critical AI upgrade may actually be a cost-effective stopgap while Apple continues developing its own model.
Siri’s Long Decline: From Pioneer to Punchline
Once revolutionary, Siri has been widely regarded as “essentially broken” and years behind competitors like Google Assistant. The gap began widening in the mid-2010s and has only grown since.
Real-World Siri vs. Gemini Showdown
In head-to-head tests comparing the iPhone 16 Pro Max and Google Pixel 9 Pro XL:
- Request: “Compare the Pixel 9 Pro XL and iPhone 16 Pro Max.”
→ Gemini: Provided a detailed breakdown of specs, similarities, and differences.
→ Siri: Returned generic Google search links. - Request: “Play the Friends theme song.”
→ Gemini: Opened YouTube Music and played “I’ll Be There for You” by The Rembrandts.
→ Siri: Opened YouTube Music but played a random song with “friends” in the title.
These failures highlight Siri’s inability to understand context or execute multi-step tasks—a core expectation of modern AI assistants.
Apple Intelligence: The Vaporware Debacle
In 2024, Apple announced “Apple Intelligence” and a rebuilt Siri with advanced capabilities like in-app actions, personal data integration, and on-device AI processing. But what users received was largely unchanged:
- Siri still defaults to Google searches for complex queries.
- Writing tools, image generation, and on-screen analysis are powered by ChatGPT, not Apple’s own AI.
- Most promised features never shipped, leading to false advertising lawsuits.
As of 2025, a new version of Siri is now expected in Q2 2026—nearly two years after the initial announcement.
Internal Chaos: How Apple’s AI Team Imploded
Behind the scenes, Apple’s AI efforts have been plagued by dysfunction:
Team Fractures and Leadership Exodus
- The AI division split into two warring factions, with the Siri team moving too slowly to modernize.
- It took two years
- In June 2025, Ruming Pang, head of Apple’s foundational AI and leader of a 100-person LLM team, left to join Meta.
- Other top AI engineers followed, accelerating the talent drain.
The ChatGPT Catalyst
The release of ChatGPT in December 2022 sent Apple’s internal teams into panic mode. Unprepared for the generative AI wave, they’ve been “floundering ever since,” unable to match the pace of innovation set by OpenAI, Google, and others.
Marketing vs. Engineering: The Blame Game
Internally, fingers are being pointed:
- The AI engineering team blames marketing for overhyping features before they were ready.
- The marketing team insists they were given optimistic timelines by engineering.
This disconnect led to a product launch built on promises that couldn’t be fulfilled—violating Apple’s core principle of shipping only polished, reliable experiences.
Failed Backup Plans: Why Anthropic Wasn’t the Answer
Before turning to Google, Apple explored a partnership with Anthropic, the maker of Claude. However, talks collapsed because Anthropic demanded too much money—reportedly more than Apple was willing to pay for a stopgap solution.
With internal development stalled and no viable alternatives, Google’s Gemini became the only realistic option to prevent further delays.
Privacy Concerns: Can Google and Apple Coexist on AI?
Given Apple’s “privacy-first” branding and Google’s data-driven business model, the partnership seems contradictory. But Apple has a plan:
“Apple believes that running the models on its own chips housed in Apple-controlled cloud servers rather than relying on third-party infrastructure will better safeguard user privacy. The company has already internally tested the feasibility of the idea.” — Bloomberg
This architecture ensures that user data never touches Google’s infrastructure, allowing Apple to maintain its privacy narrative—even if the underlying AI model is Google’s.
Do Consumers Even Want AI in Their Phones?
Despite the tech industry’s AI frenzy, consumer demand remains tepid. According to a CNET report:
| Metric | 2024 | 2025 |
|---|---|---|
| US smartphone users upgrading due to AI features | 18% | 11% |
| Users who find mobile AI unhelpful and don’t want more | — | ~30% |
This 7% year-over-year drop suggests AI is not a purchase driver. Even Samsung, which heavily promoted “Galaxy AI,” has since cited “market weakness and economic uncertainty” in earnings calls—not AI adoption—as key factors in sales performance.
What Users Actually Care About
When buying a new phone, consumers prioritize:
- Price
- Battery life
- Camera quality
AI capabilities consistently rank near the bottom of consideration lists—globally.
Apple’s Strategic Dilemma: Build or Buy?
Apple’s predicament raises a critical industry question: If you can lease a state-of-the-art AI model, why spend hundreds of billions building your own?
The Smartphone Analogy for AI
Think of AI infrastructure like a smartphone:
| Smartphone Component | AI Equivalent | Examples |
|---|---|---|
| Hardware (chips, sensors) | AI data centers & compute infrastructure | NVIDIA GPUs, cloud servers |
| Operating System (iOS/Android) | Foundational AI models (LLMs) | Gemini, GPT-4, Claude, Apple’s LLM |
| Apps (Instagram, Maps) | AI-powered applications | Siri, writing tools, image generators |
Companies like OpenAI, Microsoft, and Google are spending trillions to build both the “hardware” and “OS” of AI. But Apple may have stumbled into a smarter strategy: skip building the OS and just build better apps on top of someone else’s model.
Is the LLM Becoming a Commodity?
For everyday user requests—setting reminders, summarizing texts, playing songs—most leading LLMs perform similarly. If this trend continues, foundational models could become a commodity service, much like cloud storage or bandwidth.
In that world, Apple’s move isn’t a failure—it’s a cost-saving insight.
Samsung Already Took This Path
Apple isn’t the first. Samsung’s Galaxy AI is also powered by Google’s Gemini. This suggests a broader industry shift toward licensing best-in-class AI rather than duplicating efforts.
For consumers, the result is the same: better AI features, faster. For companies, it’s lower R&D risk and faster time-to-market.
Impact on Apple’s Business: Not as Bad as It Seems
Despite the AI stumble, Apple’s financial health remains strong:
- iPhone sales are up 29% year-over-year, driven by strong demand for the iPhone 17 in China.
- MacBook market share is slowly growing thanks to Apple Silicon’s efficiency and battery life.
- Many users are switching from Windows due to frustrations with Windows 11—including forced Microsoft accounts, aggressive telemetry, disruptive updates, and a general sense that “your desktop is the last unmonetized surface in a world that hates empty space.”
Tim Cook likely isn’t losing sleep over this AI detour. It’s a reputational hiccup, not a financial crisis.
Apple’s Philosophy: Wait, Then Perfect
Historically, Apple enters markets late but dominates through superior execution (e.g., iPod, iPhone, Watch). Their stance on AI appears consistent:
“This is new technology, automating capabilities on devices in a reliable way. Uh, no one’s doing it really well. This just doesn’t work reliably enough to be an Apple product… We don’t want to disappoint customers. We never do. But it would have been more disappointing to ship something that didn’t hit our quality standard.” — Apple Executive
In other words: Apple believes current AI isn’t ready for the Apple experience. They’d rather delay than ship a flawed product.
Why Not Ship No AI at All?
If Apple thinks AI isn’t ready, why integrate it at all? Two pressures forced their hand:
- Shareholder expectations: Investors demand AI innovation in 2025.
- Competitive pressure: Even if consumers don’t care yet, falling too far behind risks long-term irrelevance.
Hence, the Gemini deal is a strategic stopgap—buy time while perfecting their own solution for 2026 and beyond.
Broader Implications: Challenging the AI Arms Race
Apple’s move sends a powerful message to the tech industry: You don’t need to spend trillions to compete in AI.
If a company with Apple’s resources concludes that licensing is smarter than building, it could trigger a reevaluation across the sector. Startups, in particular, may focus on AI applications rather than foundational models—accelerating innovation at the user layer.
What’s Next for Apple Intelligence?
Looking ahead:
- A functional, Apple-built Siri is now targeted for Q2 2026.
- In the meantime, users will get a Gemini-powered Siri with enhanced capabilities like series summarization and multi-step planning.
- Apple will likely downplay Google’s role, emphasizing on-device processing and privacy safeguards.
The long-term goal remains clear: regain full control of its AI stack. But for now, pragmatism has won over pride.
Final Thoughts: Is On-Phone AI Overhyped?
The evidence suggests yes—for now. While AI assistants like Siri could be transformative, current implementations fall short of user expectations. And without compelling use cases beyond voice commands and text summarization, AI remains a “nice-to-have,” not a “must-have.”
Apple’s stumble isn’t just about engineering—it’s a reflection of a broader industry challenge: How do you make AI genuinely useful in a smartphone context? Until that question is answered, even the best models may struggle to justify their cost.
Join the Conversation
What do you think? Is AI in smartphones overrated? Do you care if Siri uses Google’s AI—as long as it works? Or do you want Apple to go all-in on its own model, no matter how long it takes?
Share your thoughts in the comments. And remember: sometimes, the smartest move isn’t to build everything yourself—but to know when to ask for help.
- Apple is licensing Google’s Gemini AI for Siri at a cost of $1 billion/year.
- Apple’s internal AI efforts collapsed due to team infighting, leadership exits, and technical delays.
- Only 11% of US users upgrade phones for AI—down from 18% in 2024.
- The LLM layer may become a commodity, making app-level innovation more valuable.
- Despite the setback, Apple’s core business remains strong.
This article is based on the full transcript from Cold Fusion TV’s investigative report on Apple’s AI crisis. Special thanks to Doggo and the Cold Fusion team for their in-depth analysis.
