Google Flights Adds AI-Powered Trip Finder

Google adds AI to Flights with Flight Deals

Google is rolling out an AI-powered feature called Flight Deals that helps you find cheap flights by describing the kind of trip you want. Instead of entering a fixed origin and destination, you can type things like “a weekend countryside getaway with trail rides and kayaking” or “trip to Europe with great cheese and wine in May,” and the system returns matching destinations and deals.

The tool leans on generative AI to map descriptive requests to airports, flight prices, and timing. If you don’t pick dates, Google defaults to showing flights within the next six months. You can still apply filters like maximum stops or preferred airlines, but the main value is exploratory discovery rather than fine-grained itinerary building.

In early tests the results were mixed. Searches for obvious categories, such as “a tropical destination with snorkeling,” returned predictable options like Cozumel, Nassau, and San Juan. For broader prompts, Flight Deals surfaced interesting long-tail suggestions — a “trip to Europe with hiking” yielded places like Cluj-Napoca, Romania and Ljubljana, Slovenia — which can be a welcome nudge toward lesser-known destinations.

It also stumbled. A request for a “tropical weekend trip less than 5 hours from Orlando” returned Miami and Key West, which aren’t helpful for travelers looking to leave the state. Searches like “trips to Japan during cherry blossom season” sometimes returned “no deals.” Those misses underscore that the feature is best for inspiration, not complete trip planning.

Despite limitations, Flight Deals can accelerate the early stage of trip discovery — especially for budget-conscious or undecided travelers who want ideas fast. It’s the kind of tool you might use to surface a shortlist, then follow up with deeper research and manual itinerary planning.

Why this matters

Embedding AI into discovery changes where and how travelers find options. Recommendation-driven discovery can surface off-the-beaten-path destinations, shift demand toward smaller airports, and increase overall search engagement. But it also raises product challenges: ensuring relevance, avoiding misleading suggestions, and measuring true conversion lift from “inspirational” results.

• Tune relevance: map textual prompts to meaningful destination attributes and price signals.
• Test conversion: run A/B experiments to see whether AI suggestions lead to bookings or just inspire window-shopping.
• Guard privacy and compliance: design data handling so prompts and personal preferences don’t leak sensitive information.

Accuracy matters more here than in some chat use cases. A mismatched suggestion can frustrate users; transparent signals about price certainty, dates, and deal rarity help set expectations. For travel brands that integrate similar features, blending AI recommendations with clear filters and editorial context will improve trust and usability.

Flight Deals is rolling out in beta to users in the US and Canada and is accessible from the Flight Deals page or the Google Flights menu. Expect iterative improvements as Google refines mappings between natural-language prompts and flight inventory.

How organizations should respond

Travel platforms, airlines, and tourism boards should treat AI discovery as a roadmap, not a switch. Start with small tests that evaluate relevance and bookings, instrument models to surface confidence scores, and collect qualitative user feedback on surprising or unwanted results. Consider partnerships with local tourism operators to convert curiosity into bookings for long-tail destinations.

QuarkyByte's approach is to combine product experimentation, model evaluation, and governance. We help teams define success metrics for inspiration-to-booking funnels, design A/B tests to measure revenue impact, and build data controls so personalization respects user privacy while improving deal relevance.