AI elevates customer service in travel and transportation

By Matthias Hanke, Florian Dehne and Dustin Herr

Artificial intelligence (AI) is transforming customer service in the travel and transportation industry. By automating repetitive tasks, offering real-time support and enabling hyper-personalized services, AI helps companies meet rising traveler expectations while addressing operational complexities. The sector has long embraced AI, with applications ranging from chatbots to predictive analytics already in use. Yet challenges persist. Drawing on a new survey, we explore how firms can overcome these barriers and fully harness AI to achieve operational excellence and outstanding customer experiences.

Between late 2024 and early 2025, Roland Berger, in partnership with Potloc and TalentNeuron, conducted an extensive global survey of customer service decision-makers. The cross-industry panel included 550 global managers, with around 90 working directly in the transportation sector. Their responses offer insights into the specific customer service challenges in travel and transportation, the most promising AI applications, current adoption levels and real-world use cases.

The travel industry sets the pace

Three key trends are driving the adoption of new customer service technology in the travel industry. First, demand has surged post-pandemic; four years after the outbreak, the sector has not only recovered but surpassed pre-pandemic levels, with international tourism receipts forecast to reach USD 1.6 trillion in 2024. Second, consumer expectations continue to rise. Travelers increasingly seek unique experiences and prioritize convenience, efficiency and personalization – even if they come with a higher price tag. Third, digital transformation is reshaping customer interactions; for instance, 71% of passengers prefer online or app-based booking and 53% favor airline-specific digital platforms.

These forces, working in parallel, are accelerating the sector’s openness to AI-driven technology. Compared to other industries, the travel sector shows greater readiness to adopt AI. Based on survey data, we categorize companies as “innovators,” “adopters” or “laggards.” Ten percent of respondents in the travel sector identified their firms as innovators — a higher share than in any other industry.

Current applications of AI in customer service

AI has evolved from basic automation to advanced tools like real-time assistance, dynamic itinerary planning, and personalized recommendations. While 95% of service centers have implemented AI, many still use it only for routine tasks. In travel, AI helps tailor marketing content, develop niche products, optimize pricing and streamline customer interactions. It also enables direct-to-consumer services that bypass traditional tour operators – posing strategic risks for incumbents. Yet adoption remains uneven, especially among smaller firms, due to resource constraints, process changes and challenges in upskilling the workforce.

Key challenges to AI adoption

AI adoption in customer service faces several challenges in the travel and transportation industry. Meeting diverse and fast-evolving customer expectations remains a central challenge to scaling AI effectively. In the Americas, 71% of executives identified regulatory uncertainty as a key obstacle. Risk management and lack of process design are also significant, especially in the Americas, where process rigor is prioritized. A further hurdle is the shortage of training and digital skills, particularly in Europe. The industry is also navigating evolving service models, with no clear consensus on insourcing, outsourcing or automation.

A roadmap to transformation

To truly unlock the power of AI in customer service, companies need more than isolated solutions – they need a clear, structured framework for transformation. Our recommended approach focuses on four key areas: setting a clear vision with defined AI adoption targets, value propositions and communication strategies; optimizing operations through cross-functional collaboration and strong governance; redesigning organizational setup with updated job profiles, incentives and upskilling programs; and activating key enablers like robust data governance, higher data quality and system integration. With this end-to-end strategy – supported by the right partners – businesses can boost productivity and deliver customer experiences that differentiate in a competitive market.

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