INNOVATION
The next step for AI in travel payments
As AI moves from insight to execution, travel payments must evolve to support greater automation, control, and scale. In this exclusive ITB Global Travel Collection interview, Visa shares how payment infrastructure, data, and governance are becoming critical enablers of AI-ready B2B travel commerce, with insights from Tania Platt , Global Head of B2B Travel, Visa.
Even when travellers don’t see it, agentic AI can significantly improve the experience
Q: AI is everywhere in travel right now, but what feels genuinely different about this next phase? What feels different is that AI is beginning to move beyond advising humans toward executing tasks on their behalf. We’re seeing the early emergence of agentic AI systems that can research options, apply predefined rules, and initiate transactions with human oversight. In this environment, some traditional payment approaches are increasingly challenged. Many weren’t designed for real-time decisioning, structured data exchange, or automated reconciliation at scale. As expectations shift, travel
payment models can introduce operational strain, slower settlement, manual reconciliation effort, and limited visibility into risk or working capital. These challenges become more pronounced as AI-driven systems expect faster decisioning and cleaner data flows. What’s changed most is expectation. AI-driven commerce assumes real-time authorisation, structured data, predictable settlement, and embedded controls. Intermediaries and issuers that modernise around these principles will be better positioned as AI increasingly drives B2B travel commerce.
intermediaries and issuers are looking for payment infrastructure that supports real-time authorisation, predictable settlement, and embedded controls, foundations that allow automation to scale responsibly. Q: Why are B2B travel payments at a turning point and what challenges is the industry facing? B2B travel payments were already complex, with multiple suppliers, currencies, reconciliation models, and risk profiles to manage. AI accelerates that complexity by increasing transaction volume, speed, and automation. As automation increases, legacy
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