Travel Technology

Priceline's transparency play — show users their data, let them correct it — is a direct answer to the trust problem that has slowed AI adoption in consumer travel.

If you are pitching travel AI to investors, lead with cost savings you can put on the income statement, not revenue lift you can only promise — measurability is what closes the deal.

AI has gotten remarkably good at helping travelers decide where to go. The harder problem is getting them to book. Travelport's Fahim Khan argued that as more travelers start with LLMs, pricing and transaction capabilities will need to move higher up the funnel.

The hard part of scaling AI isn't the technology, it's the people.

If your AI pilots keep stalling before production, this session argued the fix is not better models but a named owner accountable for each agent.

Acquiring a shiny company to boost your AI ambitions may seem appealing, but buying can sometimes set a company back.

What makes an offering stand out is proprietary data and operational depth that competitors can't copy.

Marriott is now in the third phase of its AI rollout, with conversational search the highest-profile launch coming this year. Its top data and AI exec says the harder work is rethinking the workflows underneath.

AI is rapidly becoming the new front door for hotel discovery, but most properties remain invisible in AI-generated recommendations. As travelers increasingly use AI early in trip planning, hotels must rethink commercial strategies, break down internal silos, and optimize for AI visibility or risk losing future demand.

When things go wrong with travel, AI agents are getting better than humans at making them right. ASAPP's case studies are evidence of the business upsides with increased cost savings and decreased errors.