InvestNot yet confirmed elsewhere1 publisher3 min readPublished
Booking's CFO says AI pays off for companies that use models and watch the bill
Booking Holdings CFO Ewout Steenbergen says AI's returns go to model users who police the bill, with chatbots referring under 1% of room nights. So far, the savings he can point to are inside the company, in customer service and engineering.
The Investor · Invest desk

What happened
- Customer service went first: bookings are growing at a high-single-digit rate while service costs are slightly down, and Steenbergen said cost per booking has fallen "by a lot."
- Booking's roughly 9,000 engineers are getting about 30% more code into production, counting only merge requests that pass testing and quality control.
- In-app AI tools show customers taking a little less time to book, converting slightly more often and cancelling slightly less, he said.
- Connected Trip transactions, where travelers book more than one travel vertical for the same trip, grew at a low-double-digit rate at Booking.com in the second quarter.
Why it matters
- decision Engineering teams are scored on cost per merge request, so Booking's token spending can keep climbing. What limits it is whether shipped code grows faster than the bill.
- capability At about 30% more shipped code, Booking's roughly 9,000 engineers turn out what about 11,700 would have at the old rate. Booking can put that extra capacity toward Connected Trip and its in-app tools.
- exposure Booking is building its AI tools for the two-thirds of customers who come to it directly. An assistant that intercepted those customers would take traffic Booking does not pay to acquire.
"I even think that the hyperscalers that spend hundreds of billions on the development of their large language models, they don't really know what is going to be the ROI," Steenbergen said at Fortune's AIQ Summit at the New York Stock Exchange [1]. His condition for everyone else is narrower. "The returns will be there for those processes that are being redesigned end to end," he said, "but you also have to make sure that those costs on the other hand are not going out of control." [3]
The work Steenbergen described at Booking is choosing models and metering them. Basic and open-source models handle simple tasks and more expensive models take the complex ones, a practice he called "effective model cost routing" [10]. Engineering groups are then measured on total IT cost per merge request, a number that adds human and AI-token costs together [11]. Token spending can go up, he said, as long as the cost of each merge request reaching production comes down [11].
The customer side rests on one number. On the August call for the second quarter, Steenbergen said referrals from large language models, paid and unpaid, were under 1% of total room nights [7]. Paid search, social media and metasearch sites bring about a third of customers, and Booking spends $8 billion to $9 billion a year on them [12]. On those two measures the paid channels are more than 33 times the size of the chatbot channel, although customers and room nights are not the same unit [20]. Booking decides where the paid money goes with constant A/B tests and large optimization models [13].
The under-1% figure can move three ways. Chatbots can stay a small source of room nights, leaving the internal savings as most of what AI returns to Booking for now [7]. They can grow as a paid channel and add another seller of traffic to a marketing bill that Booking is telling investors AI will make cheaper [18][7]. Or assistants can book hotels directly, and the referral figure would never register it, because it counts only referrals that end in a Booking room night [7].
Travelers visit about five platforms on average before booking, Steenbergen said, and AI could cut that research [14]. His case against the third outcome is about supply. "The hotel is still the hotel and the airline is still the airline and the rental car is still the rental car," he said [15]. It does not settle who keeps the customer if five platforms of research shrink to one assistant [14].
I think the evidence so far supports the cost half of Steenbergen's case and leaves the revenue half open. The counter-case is his own. He said the bigger opportunity is growth, and that AI could turn a "more transactional" Booking into "a much more high frequency business" [16]. Of the in-app tools that would have to deliver it, he said, "It's very early stage, so it's not a lot of data." [6] If customers using those tools start booking trips more often, the revenue half is proven and the cost-only reading is wrong.
What to watch
- Booking's next quarterly LLM referral figure, and whether it rises above 1% of room nights or is split between paid and unpaid referrals.
- Any figure showing Booking's cost per merge request still falling in a period when its token spending rises.
- Whether Booking's paid-marketing spend falls as a share of bookings, the cheaper-marketing claim it is making to investors.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence38
- Adoption42
- Hype gap+15
- Incentives60
- Confidence50
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- [1]
"I even think that the hyperscalers that spend hundreds of billions on the development of their large language models, they don't really know what is going to be the ROI," Ewout Steenbergen, Booking Holdings CFO, said at Fortune's AIQ Summit at the New York Stock Exchange.
ReportedSupportedSource: Ewout Steenbergen, quoted by Fortune2 sources— create a free account to open themView cited source - [2]
Steenbergen said companies that use the models rather than build them pay far less, as long as they watch the bill.
ReportedSupportedSource: Ewout Steenbergen, via Fortune2 sources— create a free account to open themView cited source - [3]
"The returns will be there for those processes that are being redesigned end to end," ... "but you also have to make sure that those costs on the other hand are not going out of control."
ReportedSupportedSource: Ewout Steenbergen, told Fortune's Sheryl Estrada2 sources— create a free account to open themView cited source - [4]
The other two-thirds of Booking's customers come directly, and Booking is building AI tools into its own apps to keep them.
ReportedSupportedSource: Ewout Steenbergen, via Fortune2 sources— create a free account to open themView cited source - [5]
Customers who use Booking's own AI tools take a little less time to book, convert at slightly higher rates and cancel slightly less often.
ReportedSupportedSource: Ewout Steenbergen, via Fortune2 sources— create a free account to open themView cited source - [6]
"It's very early stage, so it's not a lot of data."
ReportedSupportedSource: Ewout Steenbergen, on Booking's in-app AI tools, via Fortune2 sources— create a free account to open themView cited source - [7]
Steenbergen said on Booking's Q2 call in August that referrals from large language models, paid and unpaid, were under 1% of total room nights.
- [8]
Customer service went first: bookings are up at a high-single-digit rate while customer service costs are slightly down, so cost per booking has fallen "by a lot," and customer satisfaction rose.
- [9]
Booking's roughly 9,000 engineers are getting about 30% more code into production, counting only merge requests that pass testing and quality control.
- [10]
Booking uses what Steenbergen called "effective model cost routing": basic and open-source models handle simple tasks and more expensive models take the complex ones.
- [11]
Booking's engineering groups are measured on total IT cost per merge request, combining human and AI-token costs; token spending can go up as long as the cost of each merge request reaching production comes down.
- [12]
About one-third of Booking's customers arrive through paid channels such as search, social media and metasearch sites, and the company spends $8 billion to $9 billion a year on them.
- [13]
Booking runs constant A/B tests and large optimization models to decide where its paid-channel money goes.
- [14]
Travelers visit about five platforms on average before booking, and AI could cut that research.
- [15]
"The hotel is still the hotel and the airline is still the airline and the rental car is still the rental car."
- [16]
Steenbergen said the bigger opportunity is growth, not cost; Booking is "more transactional" today and AI could make it "a much more high frequency business."
- [17]
In Q2, Connected Trip transactions, where travelers book more than one travel vertical for the same trip, grew at a low-double-digit rate at Booking.com.
- [18]
Booking is telling investors that AI will make travel easier for customers and its marketing cheaper.
- [19]
About 30% more code from roughly 9,000 engineers equals the output of about 11,700 engineers at the previous rate, or about 2,700 engineers' worth of extra output.
- [20]
Paid channels bring about one-third of customers while LLM referrals are under 1% of room nights, so on these (differently measured) figures the paid channels are more than 33 times the size of the chatbot channel.
Sources
1 independent publisher whose own reporting we read for this story.
- cryptobriefing.comBooking Holdings CFO says even AI’s biggest spenders are guessing on returns
1 article · October 2, 2026
- fortune.comBooking Holdings CFO says even AI hyperscalers don’t know their ROI — but he’s learning from his ‘AI coach’
1 article · October 2, 2026
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