Dive Brief:
- Expedia Group on Monday tapped Xavier Amatriain to be its first chief AI and data officer, a title that showcases the close link between the two disciplines. He will set AI strategy and technical direction at the company, reporting to CTO Ramana Thumu.
- Amatriain brings experiences at top-tier tech organizations such as Google, where he served as VP of product for AI and compute enablement, and LinkedIn, where he led the company’s generative AI efforts. He also brings AI startup experience, having co-founded AI primary care platform Curai Health in 2017, where he served as CTO until 2022.
- “His deep expertise in building large-scale AI platforms will help redefine how people experience travel,” Thumu said in a statement on Monday. “Expedia Group operates at a scale few can match, and we invest deeply in our talent, giving technologists the space to learn, experiment, and push the boundaries of what AI can do.”
Dive Insight:
Travel planning has long been a target for disruption, swept up in the wave of digital transformation that turned every traveler into a potential critic and every homeowner into a potential host. Expedia’s hire is the latest sign of demand for further innovation in the travel industry.
Amatriain will join the company, which owns Travelocity, Orbitz, Vrbo, Expedia and Hotels.com, at a time when it has already committed to AI experimentation and deployment — and is reporting on its results. During a Q3 2025 earnings call last month, Expedia CEO and Director Ariane Gorin told investors how its three strategic priorities “continue to be accelerated by AI” and directly contributed to a 9% increase in revenue year over year.
“There is a reason why almost every generative AI demo starts with a travel planning use case — it is the perfect problem space,” Amatriain said in a LinkedIn post Monday. “But to move beyond demos and actually make travel better, you need two things: scale of data and deep domain expertise. Expedia has gathered both over many years.”
Scale of data alone, however, won’t be enough for most enterprises to see traction from generative and agentic AI projects. While Amatriain will wear a dual AI-data hat, CIOs know well that quality of data is a crucial component for any IT initiative — but especially for AI, where its output is intricately tied to its inputs.
The old IT adage of garbage in, garbage out can be a stumbling block for enterprise AI projects. In an Ocient report from October, 55% of IT and data leaders reported that data quality is the biggest barrier to AI success. In February, nearly two-thirds of data management leaders surveyed by Gartner admitted they either lacked or were unsure if they had the right data management practices for AI.
Drawing attention to this perennial problem benefits enterprises — and the tech executives helming their AI strategies. Analysts and tech leaders have laid out advice on how to determine an enterprise’s AI-readiness. And vendors are looking for ways to overcome the data management hurdle, standardizing provenance protocols and crafting a metadata framework.
