Agoda is scaling customer service with AI tools that handle routine inquiries and speed up human agents - but the company keeps people responsible for final resolutions, especially in disputes. The approach matters as the travel platform deals with rising case volumes across time zones, languages, and channels.
Complexity is the core problem, said Gauri Vicknasvaran, Senior Director of Customer Service Delivery at Agoda. Customer concerns often involve multiple parties, payment issues, booking changes, cancellations, and practical questions about properties. Partners usually raise reservation changes and cancellation policies. Resolving those fairly requires tools and defined processes that work across every channel.
Agoda's customers also expect the company to already understand their situation when they reach out. "Context, therefore, makes a significant difference to the customer service experience," she said.
Human agents work on shared platforms
Human agents operate on platforms co-developed with Agoda's product and engineering teams. That structure lets improvements launch globally instead of as isolated fixes. It connects customer service with product and marketing through shared dashboards.
"We have clear escalation paths across Legal, Security, and Data Privacy where needed, and shared dashboards give customer service, product, and marketing a common view," she said.
Customers get two front-line bots: a booking bot and a property AMA bot. These self-service tools answer questions immediately and direct users to the right support process, so every conversation starts with a human agent.
AI handles background work
Internal AI assistants help agents find answers faster. A case summarizer pulls the history of what happened and flags what to do next, cutting the time spent on summarizing. Real-time translation lets agents respond in languages they don't speak. Autocomplete drafting tools expand shorthand into clear, polite messages.
"By having real-time translation, we can substantially expand our ability to manage cases," said CTO Idan At the new Bangkok technology hub earlier this year.
The company also uses AI for language translation, so agents no longer wait for a colleague who speaks a particular language before responding. "The customer will still get clear sentences that have empathy," At the hub.
This fits Agoda's stated policy: AI handles the routine, but humans own the outcome. "AI is now a core part of how we scale support, but we always keep humans in charge of the outcome," Vicknasvaran said. That's especially important for disputes, where a technically correct answer may not produce a fair resolution. Agents retain judgment and work within policies, with AI summarizing facts and obligations.
Measuring what matters
Agoda tracks case-resolution time and customer satisfaction as its primary service metrics. The AI can improve both: self-service solves straightforward questions without queue wait, and internal assistants give agents faster access to relevant data in complex cases.
"Our aim is to surface issues early, set clearer expectations upfront, and resolve conflicts quickly and fairly," Vicknasvaran said.
Why this matters for customer support professionals
Agoda's structure shows a workable dividing line for support teams considering AI: automation handles the predictable, humans take the edge cases, and the backend connects both to a shared view of the customer. The site defines the key.
Specialists thinking about adopting similar tools will likely need a comparable internal layer - case summarization, real-time translation, and drafting assistance - not just a customer-facing bot. The company measures success by two metrics, case resolution time and satisfaction, and both improve when AI reduces the need for a customer to repeat themselves.
For support teams building their own AI for customer support strategy, the lesson is to automate what is routine, route what is complex, and keep a human review when fairness is at issue. Cases that follow that pattern get resolved faster and with better outcomes.
Senior agents and team leads who want to bridge the gaps between AI tools and human judgment can find structured training in an AI Learning Path for User Support Specialists.
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