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‘AI is Becoming a Travel Companion, Not Just a Support Tool’: Rikant Pittie on EaseMyTrip’s AI Journey
Overview:
EVA processed over 2.5 million travel interactions, showcasing growing consumer trust in conversational artificial intelligence.
EaseMyTrip combines AI with human expertise to deliver faster, contextual customer support across journeys efficiently.
Voice, multilingual capabilities, and personalization will define next-generation intelligent travel assistants for users globally.
Artificial intelligence is steadily reshaping how travelers discover destinations, book trips, and seek customer support. As conversational AI becomes more intuitive, consumers are moving away from keyword-based searches and traditional support channels, expecting faster, more contextual, and personalized assistance throughout their travel journey.
EaseMyTrip has witnessed this shift firsthand through its AI-powered assistant, EVA, which has handled over 2.5 million interactions across WhatsApp and the company's web chatbot. The growing adoption highlights increasing consumer trust in AI for everything from travel discovery and bookings to itinerary changes and post-booking support.
Rikant Pittie, CEO and Co-Founder of EaseMyTrip, believes the next phase of AI will move beyond answering questions to becoming an intelligent travel companion that understands user preferences, intent, and context, while working alongside human support teams.
In an exclusive interview with Analytics Insight, Rikant shares insights into changing consumer behavior, the challenges of building domain-specific AI assistants, the role of AI in enhancing customer engagement and operational efficiency, and how technologies such as voice, multilingual AI, and contextual personalization will shape the future of travel. Here are the excerpts from the interview:
What do Eva’s 2.5 Million AI-Led Interactions Tell Us About How Indian Consumers are Actually Using And Trusting AI Today?
The biggest insight from EVA's 2.5 million interactions across WhatsApp and EaseMyTrip's web chatbot is that Indian consumers have moved beyond experimenting with AI and are increasingly relying on it to accomplish real travel-related tasks. Whether it is discovering flight and hotel options, clarifying booking details, understanding cancellation policies, accessing offers, or resolving service-related queries, customers are turning to AI for speed, convenience, and accuracy. One trend we have consistently observed is that users no longer spend time testing whether the AI works. They come with a clear objective and expect immediate assistance.
Trust is becoming outcome-driven, with consumers focusing less on whether they are interacting with a human or an AI system and more on whether they receive the right answer quickly and reliably. What has been particularly interesting is the growing comfort with conversational search. Travelers are increasingly asking complete questions rather than typing fragmented keywords, suggesting they are beginning to view AI not just as a support tool but as a travel companion that can simplify planning and decision-making.
Why are Consumers Moving Away from Traditional Search and Support, and What do They Gain or Lose with Conversational AI Experiences?
Conversational AI is accelerating the journey by helping customers find the right information faster and complete tasks more efficiently, while human interaction continues to play a critical role in situations that require empathy, nuanced decision-making, or complex problem-solving. In travel, for instance, customers can use AI to get instant answers on baggage policies, refunds, or itinerary changes instead of navigating multiple pages, making the experience far more seamless.
The real value of conversational AI lies in reducing friction and enhancing existing customer journeys. Businesses must therefore focus on using AI as an extension of human support, ensuring every interaction remains accurate, contextual, and trustworthy.
What Makes Building Domain-Specific AI Assistants Harder Than Expected, and What Key Lessons Do Teams Learn When Scaling Them?
The biggest misconception is that deploying a large language model automatically translates into a successful customer-facing AI assistant. In reality, building a domain-specific solution requires much more than AI capabilities; it requires a deep understanding of customer journeys, business rules, operational processes, and countless real-world edge cases. That has certainly been our experience with EVA. While the underlying AI capabilities are important, the real challenge lies in ensuring the assistant understands travel-specific contexts and responds accurately to a wide range of customer needs.
Travel is not a single use case; it spans discovery, bookings, offers, itinerary-related questions, cancellations, refunds, and post-booking support, all of which require contextual understanding and seamless integration with business systems. One of the key lessons we have learned is that AI is only as effective as the ecosystem supporting it. Success depends on high-quality data, continuous model refinement, robust guardrails, and strong integration with existing systems. The real work begins after deployment because customer expectations evolve rapidly and AI systems must continuously improve to remain relevant and useful.
How are Leading Businesses Using AI to Improve Customer Engagement, Operational Efficiency, and Resolution Speed without Disrupting Existing Operations?
The most successful organizations are approaching AI as an augmentation layer rather than a replacement strategy. Instead of attempting large-scale operational overhauls, they are embedding AI into existing customer journeys and workflows to improve efficiency incrementally and sustainably. At EaseMyTrip, EVA has been designed to make travel discovery and support faster, simpler, and more intuitive. By helping customers find relevant information, access travel options, understand offers, and resolve common queries quickly, AI reduces friction across the customer journey while allowing service teams to focus on more complex cases.
What differentiates successful implementations is that AI is deeply integrated into the business ecosystem rather than functioning as a standalone tool. In EVA's case, it is connected to real travel use cases and customer touchpoints, enabling a more contextual and meaningful experience. Early indicators point towards stronger engagement, faster query resolution, and growing acceptance of AI-led travel assistance among users. The objective is not simply automation, but creating a more responsive organization that can serve customers better while improving operational efficiency behind the scenes.
What Comes After Chatbots, and How Will Personalization, Voice, and Multilingual AI Shift from Reactive Replies to Proactive Assistance?
The next evolution is not simply a better chatbot but a more intelligent travel assistant that understands context, preferences, and intent across the customer journey. Travellers increasingly expect seamless, connected experiences where they do not have to repeat information at every step, whether they are planning a trip, making a booking, or seeking post-booking support.
Through EVA and ChatGPT integration, EaseMyTrip is enabling customers to receive faster, more contextual assistance for travel planning, itinerary-related queries, booking modifications, and other routine requests, while its customer support teams continue to play an equally important role in handling complex situations that require human judgment, empathy, and personalized intervention. As customer expectations continue to evolve, capabilities such as multilingual interactions, voice-enabled assistance, smarter recommendations, and contextual support will help create more intuitive travel experiences by complementing, rather than replacing, human expertise.
