Select a question above or ask something else
What happens when AI adoption meets legacy infrastructure, fragmented data, and unclear ownership? Executives from Hilton, Marriott, Booking.com, Priceline, and more share where things stand.
In partnership with Curacity
10
Sessions covered
15+
Industry leaders featured
6%
Of hotels surface in AI search results
95%
Of GenAI projects report zero ROI
What’s inside
Infrastructure
The stack that got you here won’t scale what you’re building
Hilton and Air Canada on why modernizing core architecture has become the prerequisite — not the precursor — to AI at scale.
Distribution
Only 6% of hotels show up in AI search. That’s a revenue problem.
Curacity’s Cornell research maps how budget, aspirational, and luxury travelers use AI differently — and how early in the funnel it happens.
Agentic AI
Agents are in production. Waiting is no longer a strategy.
Sierra and Amadeus on why the companies still treating agents as future technology are already behind the ones that aren’t.
Ownership
Who owns AI once the pilot ends?
The hardest problem isn’t the technology — it’s accountability. Speakers debate why AI ownership needs to sit with the teams responsible for the outcome.
Revenue
“No one gets paid for reducing costs. You get paid for making revenue happen.”
Investors from Brook Bay Capital, Inovia, and Highgate on where AI capital is actually flowing in 2026 — and why the moat has shifted.
Personalization
Behavioral data alone is no longer enough
Priceline’s CTO on why preference data is becoming the next layer of personalization — and why letting customers see and edit that data is now a trust requirement.
“
AI search is the new front door for travel.
Nick Slavin · CEO, Curacity
Speakers
Michael Leidinger
SVP & CIO, Hilton
Firas Al Osman
Chief Digital Officer, Air Canada
Colin Coleman
SVP Data & AI, Marriott
Sejal Amin
CTO, Priceline
Vipul Hingne
Interim CTO, Booking.com
Nick Slavin
CEO, Curacity
Richard Valtr
Founder, Mews
Key data
Where AI is hitting travel hardest — and what leaders are doing about it
Themes ranked by frequency across summit sessions
Editorially assessed across all 10 summit sessions. Not a formal survey.
The technology is not the hard part anymore. The harder challenge is building a workforce that knows how to identify problems worth solving.
Colin Coleman · SVP, Enterprise Data, Analytics & AI, Marriott International
We’ve stopped thinking in terms of use cases because they often create point solutions to narrow problems.
Firas Al Osman · CDO, Air Canada
The planning-to-building ratio has inverted itself.
Sejal Amin · CTO, Priceline
Technology should help you deliver better welcomes and better goodbyes.
Richard Valtr · Founder, Mews
Read All 10 Insights — FREE
The full report covers every session, with data highlights, key recommendations, and speaker quotes.
To access Skift’s Privacy Policy & Terms of Use click here
The 2026 Skift Data and AI Summit in New York, captured in an Executive Focus Report produced with Curacity, convened senior leaders from Hilton, Marriott, Air Canada, Booking.com, Priceline, Amadeus, Tripadvisor, TUI, Cloudbeds, Mews and others to assess how AI is reshaping travel commerce. The overarching theme was a shift from experimentation to enterprise-scale execution: while roughly two-thirds of large enterprises remain stuck at the pilot stage and 95% report zero ROI from generative AI, leaders emphasized that success depends on modern cloud infrastructure, strong connected data foundations, workforce readiness, and disciplined focus on a few high-value business problems rather than scattered point solutions. A central commercial insight is that AI-driven search has become a new “front door” and distribution channel—82% of AI hotel recommendations draw from OTAs and editorial media, yet only 6% of hotels surface in AI results—forcing marketing, revenue management, distribution, and PR to converge. Debates centered on how far to optimize for AI agents versus travelers, and speakers stressed that the technology is no longer the hard part; the challenge lies in operating AI at scale through governance, monitoring, and organizational change.
Leave a Reply