Airbnb Leverages AI to Handle One-Third of Customer Inquiries
Airbnb is increasingly relying on artificial intelligence to manage customer support interactions, successfully resolving one-third of inquiries without human intervention. The company announced on February 17, 2026, that AI agents are currently handling these cases in English, with plans for global expansion throughout the year.
The move reflects a broader trend of companies adopting AI to streamline operations and improve efficiency. Airbnb intends to extend the AI-powered support to all countries where it employs human customer service representatives, anticipating a further increase in the resolution rate.
Currently, the AI assistance is limited to text-based chat support, but Airbnb is actively developing voice-based AI agents. This would allow customers to resolve issues through phone calls with an AI, marking a significant step towards fully integrated AI customer service.
The company revealed these developments alongside its quarterly earnings report last week. To bolster its AI capabilities, Airbnb recently appointed Ahmad Al-Dahle as its new Chief Technology Officer (CTO), recognizing his expertise in the field, with prior experience at Apple and Meta.
Airbnb is likewise experimenting with AI-powered search functionality, allowing travelers to find suitable accommodations through conversational interactions with an AI “lodging service.” This feature aims to enhance the user experience by providing a more intuitive and personalized search process.
According to CEO Brian Chesky, the investments in AI are not expected to have a substantial impact on the company’s profit and loss statement or capital expenditures. Airbnb is utilizing existing AI models like ChatGPT, Gemini, Claude, Kimi, and Qwen, rather than building its own models or large data centers.
This strategy allows Airbnb to quickly integrate advanced AI capabilities without the significant costs associated with developing and maintaining proprietary AI infrastructure. The company’s approach highlights a growing trend of leveraging pre-trained models for specialized applications.
