With a rich background spanning the travel, tourism, and hospitality sectors, Katarina Railko has become a key voice in navigating the industry’s technological evolution. Her insights into the intersection of technology and guest experience are particularly relevant today, as artificial intelligence reshapes how we plan, book, and experience travel. In this conversation, we explore the groundbreaking collaborations between travel giants, the profound impact of AI on personalizing and securing journeys, and how predictive technology is building a new foundation of trust with consumers. We’ll delve into the mechanics of AI-powered itineraries and discuss the future trajectory of a travel landscape that is becoming more intuitive, responsive, and intelligent every day.
We’re seeing major travel giants like MakeMyTrip, Expedia, and KAYAK unite to develop AI travel planners. What are the biggest challenges in getting these competing platforms to collaborate, and how does this combined effort practically benefit the everyday traveler looking to book a trip?
The primary challenge is navigating the deep-rooted competitive instincts that define this industry. These platforms have spent decades building proprietary data ecosystems and fiercely protecting their market share. Getting them to collaborate requires a fundamental shift in mindset from siloed competition to a shared ecosystem model. The technical hurdles are significant, involving the integration of disparate data structures and AI algorithms, but the strategic challenge of aligning business goals and data-sharing protocols without revealing trade secrets is the real mountain to climb. For the everyday traveler, however, the benefit is transformative. Imagine a world where you no longer have to open ten different tabs to compare flights, hotels, and car rentals. This collaboration creates a single, super-powered assistant that leverages the combined inventory and intelligence of all these giants. It means you’re not just getting KAYAK’s flight data and Expedia’s hotel deals; you’re getting a holistically optimized trip where all components work together seamlessly, offering a level of convenience and personalization that was simply impossible before.
MakeMyTrip is using AI to highlight hotel amenities specifically for women travelers, such as enhanced security features. Beyond safety ratings, what other specific data points can AI analyze to meaningfully improve the travel experience and safety for niche demographics like solo female travelers?
This is a fantastic application of AI that moves beyond simple booking to genuine care. While features like door eye chains are a great start, the real power of AI lies in its ability to analyze unstructured data and context. It can scan millions of user reviews for phrases like “felt safe walking at night,” “well-lit area,” or “respectful staff,” providing a nuanced understanding that a simple star rating can’t capture. The AI can also analyze location data to identify hotels that are not just centrally located, but are also close to well-trafficked public transport routes or have a higher density of open-late businesses. Furthermore, it can cross-reference hotel data with local incident reports to flag properties in areas with rising safety concerns. For a solo female traveler, this isn’t just about a lock on the door; it’s about the peace of mind that comes from knowing your entire environment has been vetted for comfort and security.
Platforms like Cleartrip and KAYAK now use AI to analyze historical data and predict future fare trends. How does this technology build trust with consumers anxious about price fluctuations, and what are the key metrics you track to measure the accuracy and success of these predictions?
This technology builds trust by demystifying the notoriously opaque world of travel pricing. For years, consumers have felt like they are gambling when booking a flight, tormented by the “what if the price drops tomorrow?” anxiety. By using AI to analyze historical data, as Cleartrip does with its 30-day look-back, these platforms are essentially pulling back the curtain. They are giving travelers a data-driven recommendation, turning a gut-feel decision into an informed one. This transparency is the bedrock of trust. In terms of measuring success, we look at a few key metrics. The most obvious is predictive accuracy—what percentage of our “buy now” or “wait” recommendations turned out to be correct? We also track user engagement with the feature and, critically, conversion rates. If we see that users who engage with the price predictor are more likely to complete a booking, it tells us the feature is not only accurate but is effectively alleviating their anxiety and giving them the confidence to click “purchase.”
AI tools can now generate complete trip itineraries, from flights to local activities, based on a user’s budget and interests. Could you walk us through the step-by-step process of how this AI curates a personalized journey, and how does it balance automated suggestions with a traveler’s desire for spontaneity?
Certainly. The process begins with the user providing a few simple inputs—let’s say, “a relaxing beach vacation in Southeast Asia for a week in March, on a $2,000 budget.” The AI first crunches the numbers on flights and accommodation, identifying destinations and lodging options that fit the budget and timeline. Simultaneously, it analyzes the user’s implicit cues—words like “relaxing” prompt it to prioritize less-crowded destinations and hotels with good reviews for their spas or quiet pools. Once the core logistics are set, the AI moves to activities, drawing from crowd-sourced data and reviews to suggest things like a sunset yoga class or a cooking lesson, rather than a crowded tourist market. To balance this with spontaneity, the AI doesn’t create a rigid, minute-by-minute schedule. Instead, it presents a curated menu of options, often clustered geographically, like “Here are three great, low-key restaurants near your hotel” or “If you have a free afternoon, this nearby national park is beautiful.” This gives the traveler a framework of high-quality suggestions while leaving ample room for them to explore and make their own discoveries.
AI travel assistants are designed to learn from user interactions to provide more refined recommendations over time. Could you share an example of how a traveler’s initial vague search could evolve into a highly personalized and complex booking, and what machine learning techniques make this possible?
Imagine a user starts with a simple search: “flights to Italy.” The AI might initially show a range of popular options. But then, the user clicks on a flight to Florence and starts looking at hotels in the Tuscan countryside, not the city center. They filter for “boutique hotels” and “vineyard tours.” The AI, using machine learning techniques like collaborative filtering and reinforcement learning, picks up on these signals. It learns this user isn’t interested in a typical city break; they want an immersive, rustic experience. On their next visit, instead of generic Italy deals, the assistant proactively suggests a travel package that includes a rental car, a stay at a highly-rated agriturismo, and pre-booked tickets to a small, local winery. It might even suggest a scenic driving route based on other travelers with similar profiles. What began as a vague query has evolved into a hyper-personalized itinerary because the AI has moved beyond keywords to understand the user’s underlying travel intent and persona.
What is your forecast for AI-powered travel?
My forecast is that AI will become the invisible, indispensable fabric of our travel experiences. The focus will shift from just booking and planning to in-trip assistance and post-trip engagement. Imagine an AI that proactively rebooks your connecting flight before you even know it’s been canceled, or that sends a notification to your phone with a suggestion for a nearby restaurant with live music, simply because it knows you love jazz. It will anticipate needs we don’t even know we have, eliminating friction points and creating moments of serendipity. The future of travel isn’t just about smarter booking; it’s about making the entire journey more seamless, intuitive, and profoundly personal, allowing us to spend less time managing logistics and more time experiencing the world.
