Google brings Personal Intelligence to Gemini users in India, four months after beta launch in US
With Personal Intelligence, Google aims to make its AI assistant Gemini more personalised by using data across apps like Gmail, Photos, YouTube and Search, enabling more context-aware responses and a seamless, integrated experience.

Last month, Google rolled out the Personal Intelligence experience to all users in the US across AI Mode in Search, Gemini on Chrome, and the Gemini app.
Eligible users will either get an invite on the Gemini home screen, or they may enable the feature manually in the AI assistant app’s Settings. Users will simply have to enable the Personal Intelligence feature and choose Connected Apps (such as Gmail and Photos). Once enabled, it works across web, Android, and iOS, and is available with all models in the Gemini model picker.
The Personal Intelligence enables Gemini to reason better across multiple sources and synthesise information from emails, photos, and online activity to deliver more tailored and context-aware responses. This reduces the need to manually search across platforms and enables a more seamless, integrated experience.
The experience is currently being rolled out to personal Google accounts of eligible Google AI Plus, Pro, and Ultra subscribers. Access to free users will be extended later.

While this may raise privacy concerns among users, the tech giant lets them choose which apps to link to power the Intelligence, to ensure a secure feature experience. By default, app connections are turned off, allowing users to enable or disable these connections at any time.
Google claims that Gemini only accesses data to respond to specific queries, and users can see or request explanations for how their information was used.
“Gemini doesn’t train directly on your Gmail inbox or Google Photos library. We train on limited info, like specific prompts in Gemini and the model’s responses, to improve functionality over time,” Google India wrote in a blog post.
Yet, the tech giant has warned that users may encounter occasional inaccuracies or ‘over-personalisation,’ where unrelated data is incorrectly linked. Users can flag and give feedback on such responses.
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