Google’s new Android Intelligence System – what it means for developers and users
During the Android Developer Summit held on 5 November 2026, Google announced a major overhaul of the way artificial‑intelligence features are built into Android apps. The company introduced the Android Intelligence System (AIS) – a platform‑wide foundation that links AI agents, such as the Gemini assistant, with the capabilities of individual apps. In practice, AIS is a set of APIs, libraries and preview programmes that let developers turn ordinary functions (checking a calendar, ordering a ride, translating speech) into agentic workflows that can be triggered either by a user’s explicit request or by the system’s proactive suggestions.
For UK Android users, the change promises more seamless, context‑aware experiences across the devices they already own – from their Pixel phone to Wear OS watches, Android‑powered TVs and even in‑car infotainment systems.
1. Connecting apps to the system‑wide Gemini assistant with Android MCP
The cornerstone of AIS is Android MCP (Model‑Calling Protocol), built on the familiar AppFunctions Jetpack library. MCP works like a universal “skill store” for AI agents:
- Remote MCP servers give developers a cloud‑based endpoint that can be called from any device, ideal for cross‑platform scenarios and for handling heavy‑weight models that don’t fit on the phone.
- Local Android MCP runs entirely on‑device, allowing fast, encrypted interactions that can tap into sensors, camera, GPS or other hardware without leaving the handset.
- When an app registers its capabilities through MCP, the system‑wide Gemini assistant (or a custom in‑app agent) can invoke those capabilities as part of a larger, multi‑step task.
Google highlighted two interaction modes:
- Prompted assistance – the user explicitly asks something like “Check my calendar, book a train, and text Emma my ETA.” Gemini then orchestrates the required calls across the relevant apps.
- Proactive assistance – the OS surfaces suggestion chips on the lock screen, in notifications or even inside the keyboard, nudging the user toward actions it predicts they’ll need.
Developers can opt‑in via the Connected Apps Platform preview to have their app appear directly in Gemini and Google Search results, turning high‑intent queries into instant actions.
2. On‑device generative AI with ML Kit GenAI and Gemini Nano 4
Google’s ML Kit GenAI received a substantial upgrade. The new Agentic API automates the classic “prompt‑then‑function‑call” loop: it stores conversation history, decides when to invoke a function, and applies built‑in guardrails to keep outputs safe. Coupled with the Prompt API (now supporting a thinking mode and system‑level instructions) developers can craft richer dialogues without writing boiler‑plate orchestration code.
A headline technical improvement comes from Gemini Nano 4, the on‑device model powering many of these GenAI features. According to Google’s internal benchmarks, Gemini Nano 4 delivers:
- ~3× faster inference than the previous Nano version, thanks to per‑layer embeddings and quantisation‑aware training.
- Up to 4× lower memory consumption, meaning the model can run comfortably on mid‑range smartphones and even on Wear OS devices.
- Compatibility with LiteRT in Google Play services, which offloads the runtime from the APK and can shave roughly 8 MB from the final app bundle.
The combination of a lightweight on‑device model and the Agentic API means developers can now build fully local AI assistants that respect user privacy while still delivering conversational fluency.
3. Hybrid cloud‑on‑device pipelines via Firebase AI Logic
For scenarios where pure on‑device inference isn’t enough – for example, when a user asks for a detailed travel itinerary that requires up‑to‑date pricing data – Google introduced Firebase AI Logic. This service lets an app call a powerful cloud model such as Gemini 4 for heavy reasoning, then fall back to Gemini Nano 4 for quick, offline tasks. Developers can protect their APIs with Firebase App Check, set spend caps, and reuse server‑side prompt templates to keep costs predictable.
4. Rendering dynamic UI with the A2UI Compose renderer
A novel addition to the toolkit is the A2UI Compose renderer, currently in alpha. It enables an AI agent to stream a JSON‑described UI that Jetpack Compose turns into native, interactive screens on the fly. In the summit demo, a “live booking assistant” generated a complete reservation flow – dates, seat selection and payment fields – without any pre‑written layout code.
For developers, this opens the door to “UI‑by‑AI” experiences where the assistant can adapt the interface to the user’s context, device form factor (phone, tablet, foldable, or XR glasses) and accessibility needs.
5. Getting started – preview programmes and resources
Google has made a suite of on‑demand videos, code samples and GitHub repositories available:
- Jetpacker sample – a reference app showing how to combine ML Kit GenAI, LiteRT and the Agent Development Kit (ADK).
- Connected Apps Platform preview – developers can enrol now, test locally with Gemini Apps Developer Mode, and later request production access once the wait‑list expands.
- AIcore Developer Preview – required to experiment with the latest Gemini Nano 4 and Gemini 4 models.
All resources are hosted on the Android Developers site, and the company encourages feedback through the usual issue trackers.
6. Why UK Android users should care
While the announcements are developer‑centric, the downstream impact will be felt by everyday Android users in the UK:
- More intelligent assistants – Expect Gemini‑driven suggestions that can book a train from London to Edinburgh, order a takeaway, or pre‑fill a form on a government website without you leaving the conversation.
- Better privacy – On‑device models mean your voice commands and personal data stay on the phone, a welcome reassurance for GDPR‑aware consumers.
- Smoother experiences on low‑end devices – The reduced memory footprint of Gemini Nano 4 means even budget Android phones can run sophisticated AI features without lag.
- Cross‑device continuity – With AIS spanning Wear OS, Android TV and Automotive OS, a single spoken request could trigger actions on your car’s infotainment system or your smartwatch, keeping the experience fluid as you move between contexts.
7. Looking ahead
Google’s push to make AI a first‑class citizen on Android mirrors the broader industry trend of embedding large language models into everyday software. For developers, the new APIs lower the barrier to creating agentic experiences that were previously the domain of large tech firms. For consumers, the promise is a more proactive, context‑aware Android ecosystem that feels less like a collection of isolated apps and more like a cohesive personal assistant.
The next few months will be crucial as the preview programmes open up, and we’ll be watching closely for the first wave of UK‑focused apps that leverage these tools – from travel planners to health trackers and beyond.
Stay tuned to Android‑Mobiles.co.uk for updates on which apps adopt the Android Intelligence System and how it reshapes the Android experience on your next contract phone.