We tested 3 AI travel agents and here’s what actually works

Vacation planning traditionally involves hours of research, comparing prices, reading reviews, and coordinating complex itineraries. Now, artificial intelligence promises to streamline this process through specialized travel agents that can generate personalized recommendations and handle booking logistics. But do these AI-powered platforms actually deliver on their promise of stress-free trip planning?

Recent testing of three prominent AI travel agents reveals significant differences in capability, accuracy, and value proposition. These platforms—ranging from established travel companies integrating AI features to dedicated AI-first services—demonstrate both the potential and current limitations of automated vacation planning.

How AI travel agents work

AI travel agents function as digital assistants that process user preferences and generate customized travel recommendations. Unlike traditional booking sites that require manual searching and comparison, these platforms use large language models—the same technology powering ChatGPT—to understand natural language requests and provide conversational planning assistance.

The systems typically integrate with existing travel databases, pulling information from airlines, hotels, restaurants, and activity providers to create comprehensive itineraries. More sophisticated platforms incorporate user reviews, seasonal considerations, and real-time pricing to refine their suggestions.

However, the quality and scope of recommendations varies significantly based on each platform’s underlying data sources and AI training.

TripAdvisor’s AI assistant

TripAdvisor, the established travel review platform, has integrated OpenAI’s generative AI technology into its existing infrastructure. The company’s AI assistant leverages TripAdvisor’s extensive database of customer reviews and travel content to provide contextual recommendations.

This integration offers a significant advantage: the AI can reference millions of authentic traveler experiences when making suggestions. For instance, when planning activities in a specific city, the system can identify highly-rated attractions while flagging common complaints mentioned in reviews.

The platform excels at providing detailed context about destinations, including seasonal considerations, crowd levels, and practical logistics. However, the AI assistant functions more as an enhanced search tool than a comprehensive planning service, requiring users to handle most booking tasks independently.

Vacay’s conversational approach

Vacay represents a newer category of AI-first travel planning services. Built on OpenAI’s GPT models, the platform offers a more conversational interface for trip planning, allowing users to describe their preferences in natural language rather than filling out structured forms.

The service provides multiple presentation formats for itineraries, from traditional day-by-day schedules to thematic groupings based on interests or travel style. Vacay’s strength lies in its flexibility—users can easily request modifications, alternative suggestions, or completely different approaches to their trip.

However, Vacay appears to rely primarily on general AI training rather than specialized travel data, which can result in generic recommendations that lack the nuanced local knowledge found in more established travel platforms. The service is currently free, making it accessible for experimental use.

Layla.AI’s premium positioning

Layla.AI positions itself as a premium AI travel service, requiring a subscription for access to its full feature set. The platform integrates data from major booking platforms including Skyscanner and Booking.com, theoretically providing more comprehensive pricing and availability information.

The subscription model suggests more sophisticated capabilities, but testing revealed significant gaps between promise and performance. While Layla.AI offers polished presentation and claims advanced personalization, the actual recommendations often lacked the depth and accuracy expected from a paid service.

The platform’s reliance on third-party data sources without clear disclosure of its underlying AI models raises questions about transparency and reliability for users making significant travel investments based on its suggestions.

Practical limitations and considerations

Current AI travel agents face several important limitations that users should understand before relying on them for trip planning:

Accuracy and real-time information: AI recommendations may not reflect current pricing, availability, or seasonal closures. Users should verify critical details independently, particularly for time-sensitive bookings or during peak travel periods.

Local expertise gaps: While AI can process vast amounts of data, it may miss nuanced local knowledge that experienced human travel agents possess, such as neighborhood safety considerations or cultural sensitivities.

Booking complexity: Most AI travel agents excel at generating ideas and itineraries but still require users to complete actual bookings through separate platforms, adding friction to the process.

Data privacy: These platforms typically require detailed personal information about travel preferences, destinations, and potentially financial data, raising privacy considerations that users should evaluate.

When AI travel agents add value

AI travel agents prove most useful for specific scenarios and user types:

Initial inspiration and brainstorming: For travelers unsure about destinations or activities, AI agents can quickly generate diverse options based on broad preferences like budget, interests, or travel style.

Complex multi-destination planning: AI excels at coordinating logistics across multiple cities or countries, suggesting efficient routing and timing that might be difficult to optimize manually.

Research consolidation: Rather than visiting dozens of websites, users can get consolidated information about destinations, though verification remains important.

Iterative planning: The conversational nature of AI agents makes it easy to refine and adjust plans, exploring alternatives without starting from scratch.

Future outlook

The AI travel agent landscape remains in early development, with significant room for improvement in accuracy, integration, and user experience. As these platforms mature, expect better real-time data integration, more sophisticated personalization, and potentially direct booking capabilities.

However, the current generation of AI travel agents works best as a complement to, rather than replacement for, traditional planning methods. Savvy travelers can leverage AI for initial research and inspiration while relying on established booking platforms and human expertise for final arrangements and complex situations.

The technology shows genuine promise for reducing the time and effort required for vacation planning, but users should approach these tools with realistic expectations and maintain healthy skepticism about AI-generated recommendations.