Google Flight Deals uses Gemini AI to plan vacations
Google's new Flight Deals feature leverages Gemini 2.5 AI to turn conversational travel ideas into real flight options, now in beta across the US, Canada, and India.
(Image credit: Google)
Google has launched Flight Deals, a new AI-powered feature that transforms vague travel ideas into concrete flight options. Powered by Gemini 2.5, the tool interprets conversational requests to find personalized flight deals, currently in beta across the U.S., Canada, and India.
How It Works
- Users can describe their ideal trip in natural language (e.g., "I want to see the Northern Lights in December")
- Gemini analyzes real-time pricing from hundreds of airlines
- Returns tailored options based on season, vibe, and preferences
"Instead of fiddling with destination drop-down menus and departure time sliders, you can simply write out the type of trip you want," the article explains. The AI considers factors like location atmosphere and flight times while searching for deals.
(Image credit: Screenshot)
Key Features
- Maintains traditional Google Flights functionality alongside new AI tool
- Ideal for flexible or indecisive travelers
- Can suggest destinations based on descriptions like "mountains and great food in spring"
Google positions this as a significant step in bringing AI to mainstream consumer applications. Flight purchases represent an ideal test case - frequent enough to be relevant but infrequent enough that users will invest time in finding deals.
The article notes that while the system is still learning, its ability to uncover unexpected deals (like cheap January flights to Oaxaca) could revolutionize travel planning.
Related Reading
- You can now edit images in Gemini directly
- I tried Gemini's new AI image generation tool
- I used Google Gemini to analyze YouTube
About the author: Eric Hal Schwartz is a TechRadar writer with 15+ years experience covering AI and technology, formerly head writer at Voicebot.ai.
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Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.