Apple and Google enter into multi-year collaboration – Performics UK give their POV on Apple and Google’s entry into a multi-year collaboration under which the next generation of Apple Foundation Models will be based on Google’s Gemini models and cloud technology.
WHAT HAPPENED
On January 12th, 2026, Google and Apple issued a joint statement announcing deeper collaboration on platform security and interoperability standards; namely the next generation of Apple Foundation Models will be based on Google’s Gemini models and cloud technology.
Apple concluded that Google’s AI technology offers the strongest platform to support Apple Foundation Models and is enthusiastic about the new, innovative experiences this partnership will enable for its users. Apple Intelligence will continue operating on Apple devices and through Private Cloud Compute, upholding the company’s leading privacy protections. While the article primarily addresses user safety and ecosystem integrity, this partnership signals a stronger
WHY IT MATTERS
• Marks a Major Realignment: A collaboration of two previously competitive ecosystems.
• Accelerates Apple’s AI Roadmap: At the same time preserving its privacy first architecture.
• Potential for New Consumer Behaviours: Introduces this across search, discovery, and device interaction.
• Privacy & Data Signals: Both companies have been tightening privacy frameworks (e.g., ATT on iOS, Privacy Sandbox on Android). A joint approach could accelerate the deprecation of cross-app tracking and further limit third-party data availability.
• Measurement Challenges: If integration standards lean towards privacy-preserving APIs, advertisers will face greater reliance on aggregated reporting and modelled conversions, reducing granularity.
• Walled Gardens Strengthening: Collaboration may reinforce closed ecosystems, making Google and Apple even more central to identity resolution and attribution. This could increase dependence on first-party data strategies.
Key Strategic Impacts
Strategic Context
- Market Momentum: Google’s Gemini signals a clear technical rebound, turning past experimentation into a credible platform that can be embedded across devices and services.
- Platform Alignment: Apple’s decision to base its foundation models on Gemini shifts the locus of foundational AI capability from multiple independent providers towards a deeper Google‑Apple interdependence.
- Product Acceleration: Apple will gain speed and capability for features like a more personalised Siri, while Google gains a high‑profile validation of Gemini’s suitability for mobile and consumer use.
Competitive Implications
- For Google: Validation of Gemini strengthens its position as a supplier of cutting‑edge models and supports the narrative that Search remains central to AI distribution and monetisation.
- For Apple: Faster feature rollout and improved AI experiences, but a reduction in exclusivity over core model technology and increased reliance on an external provider.
- For Competitors: Competitors that supply models or cloud services now face a landscape where Google has both a technical and distribution advantage, forcing them to emphasise differentiation in pricing, privacy, or specialised capabilities.
In Market
- Durability: Gemini’s adoption by a major partner like Apple suggests Google can continue to funnel AI usage through Search and related surfaces, supporting ad and cloud revenue pathways.
- Risk: Investors may view Google as having regained momentum in the AI race, which could lift confidence in long‑term revenue but also invite closer regulatory scrutiny.
- Value Drivers: Expectations for recurring cloud revenue, model licensing, and expanded ad inventory tied to AI interactions may become more prominent in revenue forecasts.
Risks
- Partner Dependence: Apple should negotiate scalability, pricing caps, and audit rights to reduce risk.
- Privacy Perception: Apple must clearly document and demonstrate how on‑device and Private Cloud Compute protections prevent user data from being used to train external models.
- Regulation: Apple and Google should prepare coordinated compliance playbooks and transparent reporting to address antitrust and data‑protection inquiries.
What does this mean
Channel Impact
Paid Search
Expect continued push towards Privacy Sandbox solutions (Topics API, Protected Audience). Attribution windows and remarketing pools may shrink further.
Paid Social
Platforms will feel pressure as signal loss deepens. CPMs could rise due to reduced targeting efficiency.
Programmatic
Contextual and publisher first-party data will gain importance. DSPs may need to integrate with new APIs for conversion measurement.
SEO
Minimal direct impact, but any browser-level changes (e.g., cookie handling) could affect analytics and organic performance tracking.
Potential Risks
Regulatory Scrutiny
EU regulators may view this alliance as anti-competitive, which could lead to delays or forced adjustments.
Advertiser Cost Inflation
Less precise targeting often drives higher acquisition costs
What should you do now?
Recommended Actions
Double down on first party data
CRM integration, consent strategies, and clean rooms will be critical
Test privacy-compliant measurement tools
Google’s attribution APIs, Apple’s SKAd Network
Scenario planning for signal loss
Build models for performance under reduced targeting precision
Publicis POV
Our platform agnostic stance remains; we evaluate based on performance, transparency and clear value.
This partnership is a technological shift, not an immediate advertising shift, but it does set the stage for future opportunities.
Implications:
- We expect more contextual, conversational and AI-driven user journeys within the Apple ecosystem.
- A more capable Siri may influence search pathways, content navigation and brand discovery.
- Privacy constraints remain unchanged – limited user level data, but richer contextual signals may emerge.
A broader strategic consequence is that Google has rapidly closed the AI gap with its Gemini models after earlier setbacks such as Bard. Apple, which previously leaned on ChatGPT as its preferred intelligence engine, is now aligning its next‑generation Apple Foundation Models with Google’s technology. Gemini’s emergence as a leading large language model for mobile devices reinforces confidence that Google can preserve the distribution power of Search and convert that reach into long‑term monetisation.
Takeaway:
Google’s Gemini has materially narrowed the AI gap, and Apple’s adoption both accelerates consumer AI features and reshapes competitive and investor expectations about who controls the foundational layer of mobile AI.