# How Expedia Group Builds AI That Lasts at Scale

DevFeed: [How Expedia Group Builds AI That Lasts at Scale](<https://devfeed.tech/articles/how-expedia-group-builds-ai-that-lasts-at-scale-19733.md>)

Original publisher: [Read original article](<https://medium.com/expedia-group-tech/how-expedia-group-builds-ai-that-lasts-at-scale-434677770fe9?source=rss----38998a53046f---4>)

Author: Xavier Amatriain

Published: 2026-07-14T11:01:01Z

Content type: opinion

Language: en

Sources: [Expedia](<https://devfeed.tech/sources/expedia.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Strategy](<https://devfeed.tech/topics/ai-strategy.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [Development](<https://devfeed.tech/topics/development.md>), [sdlc](<https://devfeed.tech/topics/sdlc.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [data](<https://devfeed.tech/tags/data.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [generative](<https://devfeed.tech/tags/generative.md>), [governance](<https://devfeed.tech/tags/governance.md>), [innovation](<https://devfeed.tech/tags/innovation.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [recommendations](<https://devfeed.tech/tags/recommendations.md>), [sdlc](<https://devfeed.tech/tags/sdlc.md>), [software-engineering](<https://devfeed.tech/tags/software-engineering.md>), [tooling](<https://devfeed.tech/tags/tooling.md>), [use-cases](<https://devfeed.tech/tags/use-cases.md>)

## AI overview

Expedia Group describes a framework for building, deploying, and evolving AI systems that remain reliable and scalable over time. The article emphasizes principles covering business value, ownership, governance, evaluation, safe rollout, and monitoring, and describes Agentic Release tollgates that translate those principles into launch checks integrated with the SDLC.

## Source excerpt

Expedia Group Technology -- InnovationA framework for how we build, deploy, and evolve AI systems for impact and scalePhoto by Florian Wehde on Unsplash There's an important distinction between Artificial Intelligence (AI) that just works today and AI that lasts at scale. Many companies optimize hard for the first one without ever asking whether they're building the second. Velocity without discipline and strategic direction is a liability, not an asset. The hardest part of building AI at scale isn't getting a model to work once. It's building systems that continue to work, scale beyond individual teams and use cases, and improve consistently over time. Today's AI systems do more than just predict and optimize. They converse, reason, and increasingly take action. An autonomous system making decisions on a traveler's behalf creates a very different set of expectations around reliability, governance, and accountability. As AI takes on more of those roles, the principles behind how these systems operate matter more than ever. At Expedia Group™, we have spent years applying AI and machine learning across the traveler journey from personalization, ranking, and recommendations, to fraud prevention, customer support, and, more recently, generative and agentic AI experiences. That depth of experience is what led us to develop a set of machine learning and AI principles to guide how we build, deploy, and evolve AI systems across the company. The goal is simple: make sure the systems we build create real business value, scale across the company, and operate safely. These principles define how we measure, design, govern, and operate the systems we use. From principles to practice Publishing principles is the easy part. The harder and more important work is turning them into operating mechanisms: recommendations, requirements, tooling, and release processes that teams actually use. At Expedia Group, we have started doing this through Agentic Release tollgates: a set of recommend