Travel planning used to start with tabs, filters, and endless scrolling, the familiar ritual of comparing photos, prices, and reviews until decision fatigue set in. That habit is already slipping. A new joint analysis by NYU School of Professional Studies and Boston Consulting Group suggests that 37% of travelers are now using AI-powered large language models embedded directly into travel platforms to plan and book trips, turning discovery into a conversation rather than a hunt. Ask instead of search. Shortlist instead of scroll. It sounds subtle, but it changes almost everything about how hotels are found, chosen, and remembered.
What makes this shift especially interesting for travelers is that it’s happening right where booking decisions already occur, inside online travel sites rather than in some futuristic standalone app. As AI assistants synthesize reviews, pricing, location, amenities, and even past preferences, they surface only a handful of recommendations. That compression matters. Hotels are no longer competing for page-one placement or banner ads alone; they are competing to be deemed relevant by an algorithm that decides what even gets mentioned. The old OTA tradeoff hasn’t disappeared either. Commissions still hover between 15% and 30%, but now prominence itself is becoming a priced input, bundled into AI-driven recommendation systems where visibility is negotiated in new, less transparent ways.
Behind the scenes, the pressure on hotels to adapt is intense, and not just because of distribution. In North America, 65% of hotels reported staffing shortages in 2025, while labor costs jumped 11.2% year over year. For guests, this often shows up as longer waits, reduced services, or leaner operations. For operators, it’s a math problem that no longer balances. The report makes a quiet but persuasive case that AI isn’t a shiny add-on here; it’s becoming economic infrastructure. Early deployments already show practical gains, like room turnaround times improving by roughly 20% through AI-synchronized housekeeping schedules that align checkouts with real staff availability. In kitchens, AI-driven waste tracking has cut food waste by about half within months, which is the kind of improvement that doesn’t just help margins, it changes how sustainably a hotel can operate day to day.
All of this depends on something travelers rarely see but increasingly feel: data coherence. Many hotels still run on fragmented systems that don’t talk to each other very well, making it hard to present a consistent, trustworthy digital presence. Nearly half of hoteliers say accessing critical information remains difficult, which is a problem when AI assistants are pulling answers from everywhere at once and rewarding clarity and consistency. There’s also a human gap. Only about 2.9% of full-time workers in travel and tourism currently have AI skills, a striking contrast to tech and media, even though AI-related roles in hospitality are growing steadily. The implication for travelers is subtle but important: the best future experiences will likely come from hotels that invest not only in smart tools, but in people who know how to shape them.
For anyone planning trips in 2026 and beyond, this shift explains why recommendations are starting to feel more curated, more confident, and sometimes oddly decisive. The shortlist you see is no longer just popular; it’s algorithmically justified. Hotels, meanwhile, are learning that discovery now happens in dialogue, not directories. The ask-and-book era is arriving without much fanfare, but once you notice it, it’s hard to unsee.