Making 600 Billion Decisions With AI: Expedia Group’s Rathi Murthy

**Sam Ransbotham** (0:02)
When consumers plan travel, they consider many factors.
They don't make 600 billion decisions, but one travel company's AI tools do. Find out how this company is modernizing the travel industry on today's episode.

**Rathi Murthy** (0:17)
I'm Rathi Murthy from Expedia Group, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:24)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI.
I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy guest editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:43)
And I'm Shervin Khodabandeh, senior partner with BCG, and one of the leaders of our AI business. Together, MIT SMR and BCG have been researching and publishing on AI since 2017
Interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.

**Sam Ransbotham** (1:10)
Welcome. Today our guest is Rathi Murthy, CTO and president of Expedia Product and Technology.
Rathi, thanks for taking the time to talk with us.

**Rathi Murthy** (1:18)
Very excited to be here. Thank you for inviting me.

**Sam Ransbotham** (1:22)
There's so many places that we could start, but maybe we start with Expedia. We've got listeners throughout the world who may not be familiar with Expedia, or they may know Expedia, but not the Expedia Group.
So maybe let's start there. Can you describe Expedia for us? What are the things your group does?

**Rathi Murthy** (1:38)
Sure. At Expedia, I am the CTO, and I manage product and technology for Expedia Group. If you think about Expedia, we started as a family of 21 different brands, and today we are bringing all of these brands together and building a platform for travel.
And some of the brands, well-known brands, across everything is really Expedia, hotels.com, Vrbo, Travelocity. And what we are trying to do is unify these experiences and bring common building blocks that can help us transform not just Expedia, but transform the travel ecosystem altogether.

**Shervin Khodabandeh** (2:22)
So Rathi, put this in perspective for our listeners, right? There must be a huge scale and traffic of travel, like globally a day. Can you give us some quantification of the scale that we're talking about here? Like flights, hotels, reservations, the complex network of travel options. How big is that scale?

**Rathi Murthy** (2:44)
Yeah, totally. So if you think about our business, today we connect over 168 million loyalty members across all these brands and 50,000 B2B partners with over three million properties and over 500 airlines, car rentals, cruise lines. And when you think about the data that we have across all these brands and on our platform, today we process over 600 billion AI predictions a year.
It's powered by over 70 petabytes of data. So just think about the gamut of data and the volume of business we run on our platform to service travel across all these different lines of business, whether it's lodging, air, car or cruise.

**Shervin Khodabandeh** (3:38)
And what are some of these AI decisions? Give our listeners some examples.

**Rathi Murthy** (3:42)
Sure. Fundamentally, I believe as technology, AI can be leveraged across almost all aspects of running our business. There are some core platform capabilities that we excel at leveraging complex AI and ML, one being fraud prevention. Now, everybody has fraud prevention in many, many sectors, like finance, you have things where you see a stolen card or account takeover, and that's a very common use case of being able to detect fraud as you see attacks. But in travel, it gets even more complex. We're looking at preventing abuse of trust, which impacts the safety of all our travelers, especially when you think about vacation rentals. Now, abuse can be anything from fake reviews, bad listings, inappropriate content, wrong images, descriptions, or even improper use of a property, whether there's illegal activity, too much noise. We have to protect against all these scenarios. And what makes it super difficult is there's a very little time between a booking and the time that a person takes a vacation. And our algorithms have to be able to find these variants that differ from the normal track and alert us of any of these signals so we can go address this and protect our travelers.
That is one aspect. And we have excelled at this. We're really good at being able to alert. The complexity is also that we don't own the end service. That is the hotel or the vacation rental or the flight. So we must apply a higher level of sophistication to our technology and data science capabilities to protect our travelers, our supply partners, and on our platform. That's one aspect, if you think about it at the platform level.