Google Developing AI Agents for Gemini App to Automate Mobile Tasks

Google Developing AI Agents for Gemini App to Automate Mobile Tasks

AI agents are intelligent software systems designed to independently plan and make decisions to complete tasks based on user commands. Google is preparing to introduce such agents on mobile devices through its Gemini platform, enabling tasks such as ticket bookings and online shopping to be completed without opening individual apps.

Google is developing AI agents within the Gemini app for mobile users, a move that could significantly change how smartphones are used. The technology is designed to understand voice or text commands and automatically connect with relevant applications to complete required tasks. According to reports, Google may present this feature at its I/O event in 2026, with an initial rollout expected to begin on Pixel devices. The stated objective is to make digital tasks faster, simpler, and fully automated.

AI agents are software systems capable of understanding assigned tasks and independently planning the steps needed to complete them. They are built with reasoning, planning, and memory capabilities, allowing them to improve performance over time. For example, if a user requests a train ticket booking for the same evening, the AI agent would open the appropriate platform, check seat availability, complete the payment process, and provide confirmation, without requiring the user to navigate apps or fill out forms.

Google aims to establish Gemini as the primary AI assistant across its devices. AI agents form a central part of this strategy, enabling users to complete most digital tasks directly through AI-driven commands. According to reports, the company plans to officially introduce this technology at its upcoming I/O 2026 event.

For users, AI agents are expected to reduce the time and effort required to complete digital tasks. The need to repeatedly open apps, log in, or manually enter payment details could be significantly reduced. These agents may also be able to make personalized decisions by learning user preferences, such as selecting the most affordable platform, the most suitable time, or preferred seating options.

 

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