Gemini Automations on Android: What’s New and What It Means

Google has released a suite of updates that expand Gemini-powered capabilities on Android. The headline feature is a beta for on-device automations that can complete multi-step tasks—like ordering food or booking a ride—on behalf of users. Alongside these automations, Google is rolling out broader scam detection for calls and messages and improving its Circle to Search tool so it can recognize and query everything on a phone screen at once. These changes point to a broader shift: mobile AI moving from single-query assistants to task-oriented automation while putting privacy and user control front and center.

What are Gemini automations on Android and how do they work?

Gemini automations on Android are AI-driven workflows that string together multiple app actions to complete real-world tasks. Instead of asking the assistant to perform a single step, users can instruct Gemini to execute a sequence—search for a nearby restaurant, place an order, and schedule a delivery window—without manually switching between apps.

Core behavior and constraints

• Beta availability: The automations are initially available in beta and restricted to select apps in food, grocery, and rideshare categories.
• Device support: Launch devices include select flagship phones, and availability is staged by region.
• Explicit activation: Automations require a clear, explicit command from the device owner to start.
• Real-time monitoring: Users can observe the automation’s progress and cancel if it makes a mistake.
• Scoped access: Automations run inside a secure, virtual window that limits what apps and data the AI can access.

These design choices prioritize predictability and safety while enabling assistants to handle more complex, practical chores for everyday users.

Which devices, apps, and regions are supported?

The initial rollout targets recent flagship smartphones and a narrow set of app categories: food delivery, grocery services, and ridesharing. Support is limited at first to specific regions. Expect gradual expansion based on developer integrations, user feedback, and regulatory or safety considerations.

Developer and platform implications

For app developers and platform teams, the automation feature creates both opportunity and obligation. Integrating with automations can increase order volume and engagement, but apps must expose reliable, robust APIs and predictable UI surface areas for the assistant to manipulate. Developers should consider how to:

1. Provide machine-friendly endpoints and intents for common tasks.
2. Design confirmation UX to prevent undesirable orders or bookings.
3. Instrument observability to trace automation flows and manage errors.

For a deeper read on building AI-native app infrastructure and operational patterns, see our guide on AI App Infrastructure: Simplifying DevOps for Builders.

How does Google protect users from automation risks?

Automations introduce new attack surfaces and failure modes—incorrect orders, unexpected charges, and privacy leaks are real concerns. Google implements a layered protection model:

• Opt-in triggers: Automations cannot begin without an explicit instruction from the device owner.
• Live supervision: Users can view progress as the workflow runs and interrupt the task at any time.
• Scoped execution: The automation executes in a sandboxed window with limited access to apps and data, reducing the chance of broad data exposure.
• On-device safeguards: By leveraging on-device models for sensitive detection tasks, personal data can be processed locally rather than always sent to cloud services.

If you’re interested in practical protections for multi-agent and automation systems, our coverage of industry best practices explores risk mitigation in more detail: AI Agent Security: Risks, Protections & Best Practices.

What’s improved in scam detection and messaging safety?

In addition to automations, the update expands scam detection features across calls and texts. On-device models now flag suspicious calls and texts, helping users avoid scams without routing sensitive content to remote servers. Expansion plans include additional handset families and geographic regions over the coming months.

Why on-device scam detection matters

On-device detection reduces latency and privacy risk while enabling immediate, contextual warnings. This is particularly useful for phone-based fraud that exploits immediacy—scam calls, urgent fake notices, and text-based phishing. Real-time alerts let users act before personal data or money is exposed.

How has Circle to Search evolved?

Circle to Search is moving beyond single-object queries. Now you can gesture around multiple items on your screen and ask the assistant to identify everything in the region—outfit components, product groups, or a collection of visual elements—to surface aggregated information and related topics.

Practical examples

• Fashion discovery: Circle an outfit photo to get product matches for each clothing item and accessories.
• Product research: Select a shelf of products to compare specs and price ranges across the items you see.
• Contextual learning: Circle multiple diagrams or images in an article to pull together a single, concise summary.

Limitations and real-world expectations

Despite the promise, current automations and on-device features are intentionally constrained:

• App coverage is narrow at launch—expect greater breadth only after developers build integrations and partners validate flows.
• Geographic and device availability is phased; not all users will see features immediately.
• Complex, multi-party tasks (for example, coordinating across many services with billing or identity verification) remain challenging.

These limitations reflect a cautious, iterative approach: enable high-value tasks first, measure safety and reliability, then broaden capabilities.

Where does this fit in the larger trend toward task automation?

Mobile automations signal a shift from reactive assistants to proactive, task-completing systems. From calendar management to routine purchases, AI that reliably and safely executes sequences can save users time and reduce friction. The real winners will be experiences that combine clear user intent, confirmations that prevent errors, and transparent controls for privacy.

Opportunities for businesses and builders

Companies that align their product flows with automation patterns—standardizing endpoints, providing clear user confirmations, and enabling failure recovery—can tap into new conversion channels. Builders should also design for observability and testability so automation runs can be audited and improved over time.

For perspective on how AI agents are being applied to enterprise workflows and automation, consult our analysis of agent platforms and workflow integrations: Google Opal Agents: Build Automated Workflows with Gemini.

How can users prepare and protect themselves?

If you see automations arrive on your phone, follow these practical steps:

1. Review permissions and grant only what is necessary for the task.
2. Use confirmation prompts to catch errors before they result in charges or commitments.
3. Monitor automation history and logs to learn how workflows behave over time.
4. Keep device software up to date to receive the latest security and privacy improvements.

Will automations replace manual control?

No—at least not yet. Automations are designed to augment user control, not remove it. By default they require explicit activation, provide live feedback, and can be canceled. The goal is to reduce repetitive friction while preserving transparency and user agency.

Key takeaways

• Gemini automations on Android bring practical multi-step task automation to mobile users while operating within strict safety and privacy boundaries.
• Expanded on-device scam detection and the broadened Circle to Search improve usability and safety for everyday mobile interactions.
• Initial rollouts are intentionally narrow; expect broader app and regional support as the ecosystem matures.

Next steps for readers

Watch for updates from your device maker and app providers. If you’re a developer, plan integration points and build robust confirmations. If you’re a user, experiment with limited automations first and use the pause/cancel options as you gain confidence.

Call to action: Want in-depth coverage and practical how-tos for mobile AI and automation? Subscribe to Artificial Intel News for weekly analysis, guides, and product deep dives. Try the new features when they arrive and share your experiences—your feedback will shape safer, more useful automations for everyone.