Expedia Group Details AI Lessons Learned From Early Chatbot Efforts

Artificial intelligence (AI) has become a central focus for travel companies seeking to improve customer experience and operational efficiency. Expedia Group has moved quickly to adopt AI technologies. However, the company’s journey has revealed both opportunities and challenges, particularly in customer trust, organizational change, and the practicalities of implementing new technology.

Early Chatbot Experiments and Lessons Learned

Expedia Group began testing AI-powered chatbots two to three years ago, aiming to create a more conversational booking experience for travelers. In 2024, the company publicly launched Romie, an AI assistant designed to help users with their travel needs. However, the chatbot was eventually discontinued after the company observed key issues.

According to Shilpa Ranganathan, Expedia Group’s chief product officer, the main challenge was maintaining traveler trust. At a recent industry summit, she explained that users quickly lost confidence if chatbot responses were not grounded in accurate data, such as real-time inventory and reservation rates. When customers felt the chatbot was not providing reliable or relevant answers, they were likely to abandon the service.

This realization prompted Expedia Group to reassess its approach. The company shifted focus from rapid deployment to building a robust AI framework and platform. This included developing better evaluation methods for AI outputs and creating scalable architecture to support future AI agents. Ranganathan noted that while this approach may appear slow from the outside, it is necessary to avoid building on an unstable foundation.

Low Barriers and the Importance of Experimentation

Despite the challenges, Ranganathan emphasized that the barrier to starting new AI projects is relatively low. This accessibility allows employees across different functions to experiment and learn from AI applications. However, she cautioned that not all experiments will lead to successful outcomes.

Ranganathan stressed that the ultimate measure of success is customer adoption and satisfaction. While encouraging a culture of experimentation is important, the company must ensure that new AI features genuinely address customer needs. She pointed out that travelers are less concerned with the technology itself and more focused on whether their travel arrangements are handled efficiently.

Organizational Change and Employee Engagement

Adopting AI is not just a technical challenge; it also requires significant organizational change. Ranganathan identified change management as a critical factor in successful AI integration. She spends considerable time working on culture management, aiming to empower employees to take risks and experiment with new tools.

One complication is the cost and accessibility of AI tools. Ranganathan explained that democratizing access is essential for encouraging employees to change their behavior and embrace new technologies. To address this, Expedia Group has focused on creating the right “scaffolding” to support experimentation while managing costs and risks.

Focus on Customer Outcomes

Throughout the AI adoption process, Expedia Group has consistently prioritized customer outcomes. Ranganathan reiterated that experimenting with AI is only valuable if it leads to solutions for real business problems. Without a clear link to customer needs, even the most innovative AI projects are unlikely to gain traction within the company or among travelers.

Conclusion

Expedia Group’s experience with AI demonstrates the complexities involved in integrating new technologies into established business models. The company’s early chatbot trials highlighted the importance of trust and data accuracy, while ongoing efforts have focused on building a strong technical and cultural foundation. As AI continues to evolve, Expedia Group’s approach underscores the need for careful planning, employee engagement, and a relentless focus on customer needs.

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