How AI is quietly transforming corporate travel
Forget flashy chatbots — the real AI revolution is in cleaning messy data and enabling personalized insights for travel managers
AI may dominate headlines with futuristic promises, but in corporate travel, the real action is far from the spotlight. At major travel management companies like BCD Travel, American Express GBT, and Amadeus, AI is less about slick automation and more about laying the groundwork: cleaning data, improving reconciliation, and slowly building toward personalization and efficiency. While the industry's ambitions are high, most players admit they're only at the beginning of the journey.
Key takeaways
BCD Travel: Focus on data infrastructure
- BCD’s AI work centers on improving data ingestion, quality, reconciliation, and client-specific insights.
- Key challenge: highly fragmented data from disparate sources like GDSs, booking tools, and card providers.
- Example: AI-assisted credit card reconciliation and extracting insights from unstructured data (PDFs, comments, etc.).
- Goal: Enable clients to interact with data directly and create customized dashboards and predictive alerts.
Personalization is the future, not automation
- BCD believes AI’s biggest impact will be in empowering users across departments to gain tailored insights.
- Singh (BCD) stresses that clean data is the foundation—AI without it is ineffective.
Amex GBT: Supporting agents, not replacing them
- AI is used to surface policy rules for travel agents, improving response speed and compliance.
- A customer-facing chatbot handles FAQs but is only 60% accurate—complex tasks still need humans.
Amadeus: Testing “Agentic AI” and natural language queries
- Amadeus is exploring modular AI agents and tools for voice and natural language interactions.
- Current tools can answer simple queries, but full automation is still years away.
Overall industry mood: AI is still in its early days
- Despite bold visions, leaders agree the industry is in the early innings of AI adoption.
- Clean, actionable data remains the critical bottleneck for progress.
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