Google enables Gemini to tap Gmail and Photos for more accurate, personalized answers

Google has made Gemini significantly more useful for everyday tasks: the Personal Intelligence feature allows the assistant to connect to Gmail, Google Photos, search history, and other services to understand context without lengthy explanations. In practice, this means the chatbot can suggest more accurate purchases, provide specifications for a device you've already bought, or gather trip ideas even if the user didn't mention key details in the request itself. The essence of the feature is that Gemini begins to rely not only on the prompt formulation but also on data from connected Google apps.

To enable it, go to Gemini settings on the web or mobile app, open the Personal Intelligence section, enable memory of past chats, and separately select which services can be used. These include Gmail, Calendar, Docs, Drive, Google Photos, Search, YouTube, Google Home, and YouTube Music. As of March 2026, Google has begun expanding access to the feature for free users in the US; previously it was only available to AI Pro and AI Ultra subscribers.

However, it only works with personal Google accounts, not corporate or educational Workspace. One of the most telling tests involved ordinary shopping. The author entered a simple request about summer toys for a child, deliberately not specifying age, gender, or even city.

Gemini immediately responded as if it already knew the situation: mentioned the daughter, her age, and the regional climate conditions, then suggested suitable options like water tables and sprinklers for hot and humid weather. The selection even included stylistically similar options that, by the author's impression, matched previous interests and purchases. This is the main effect of Personal Intelligence: instead of averaged results, the user gets answers assembled based on their digital traces within the Google ecosystem.

The second test showed how this works in a more practical scenario. Through Gemini in Chrome, the author asked what tire size was needed for her pickup truck without naming the model. The service responded with specifics: named the 2017 Ram 1500 Quad Cab, clarified that tire size depends on configuration and installed wheels, and offered two factory options.

Additionally, Gemini explained where to check exact data — on the sticker in the door jamb on the driver's side or on the sidewall of the current tires. For the user, this saves time: no need to search through old emails, receipts, or photos to restore basic context before asking a question. The third example relates to trip planning.

In AI Mode in Google Search, the author asked for suggestions about interesting activities near a summer camping location without naming the region or dates. Gemini managed to connect data from documents and other services, understood the conversation was about the Thousand Islands area on the US-Canada border, and suggested ideas relevant specifically to July 2026: waterfront festivals, live music, Fourth of July fireworks, Antique Boat Show, and a trip to Boldt Castle. If Autobrowse mode is enabled in Chrome, the next step can be done right there — ask Gemini to add these activities to an existing route document or create a new one.

This leads to broader scenarios. Personal Intelligence can adjust answers based on reading and search history, YouTube habits, emails, photos, calendar events, and Drive documents. Because of this, Gemini better handles not only shopping or travel but everyday tasks like comparing prices, local recommendations, device diagnostics, or even discovering new hobbies.

The main advantage is a sharp reduction in friction: instead of lengthy prompts with biography, preferences, and a listing of past actions, a short request is sufficient. But the price for such comfort is obvious: the user allows AI to access deeper into their personal data layer. Google emphasizes that the feature is voluntary, all connections can be manually enabled and disabled, and activity can be deleted.

In Gemini's reference materials, it also states that personal content from connected Google services is not used for training generative models and is not applied for displaying ads, although the service itself can access this data when responding to requests. In practical terms, this is an important turn for the market: Google is betting not just on model strength but on the advantage of its own ecosystem. The better Gemini knows the user, the more useful it becomes — and the stronger the dependence on Google services grows.