Why Hotels Are Investing in AI Before They Know the Full ROI

More than half of hotels now use or are procuring generative AI. Fewer than one in ten of them can point to a measurable 30% drop in manual work because of it. That gap, published this month by NYU’s Jonathan M. Tisch Center of Hospitality alongside RateGain and HEDNA, is the actual state of hotel AI adoption right now. Hotels aren’t waiting for proof the investment works. They’re making it anyway.

The Adoption Number That Hides the Real Story

The State of Distribution 2026 report drew on data from over 270 hotel brands and 58,000 properties across 141 cities. Its headline finding sounds like a success story: generative AI use has crossed the halfway mark across the industry. Its second finding complicates that story considerably. Fewer than one in ten hotels report a reduction in manual work above 30% as a result.

The report’s own explanation isn’t a technology problem. It’s trust. Hotels are willing to let AI assist with a task. Far fewer are willing to let it act autonomously, and that hesitation caps how much of the manual workload actually disappears. A tool that drafts a report still needs someone to review it. A chatbot that handles simple guest questions still routes anything complicated to a person. The technology is present. The autonomy it would need to fully replace the manual step mostly isn’t there yet.

The same report puts a number on exactly how much manual work is still absorbing hotel commercial teams. More than 80% of commercial teams still spend one to two days a week producing and analyzing reports manually, and fewer than 30% have invested in dedicated reporting tools. That’s the specific workload AI is supposed to be eating into, and it’s largely still there, sitting underneath adoption figures that look impressive on their own.

Confidence Hasn’t Slowed Down to Match

What’s notable is that this gap hasn’t dented hotel confidence in AI as an investment. A separate global survey from Canary Technologies, covering more than 400 hotel and hospitality technology decision-makers, found that 85% plan to allocate at least 5% of their IT budget to AI tools this year. Seventy-one percent already describe AI’s impact on the industry as significant or transformative, and 82% expect their own AI usage to expand further within the next year.

Read next to the NYU findings, this isn’t a contradiction so much as a pattern that shows up whenever a new operational technology arrives ahead of the trust needed to fully exploit it. Online distribution went through something similar in the 2000s. Revenue management systems went through it in the 2010s. In both cases, the properties that invested early, before the systems were fully mature and before the returns were fully provable, ended up with a structural head start once the technology caught up to its own promise.

That pattern matters more than the specific percentages, because percentages shift every quarter and the underlying dynamic doesn’t. A technology curve doesn’t wait for universal proof before it starts rewarding early movers. It rewards the properties that build the operational muscle, clean data, trained staff, defined governance, while the technology itself is still catching up to its promised ceiling. By the time the ROI case is undeniable to everyone, the early movers already have a multi-year head start on the operational side that a spreadsheet comparison won’t capture.

Why Investing Before Proof Isn’t the Same as Investing Blind

There’s a real difference between investing ahead of proof and investing on faith. The hotels expanding AI budgets right now aren’t doing so in a vacuum. They’re doing it with visibility into where the technology already delivers, guest messaging, drafting, first-pass reporting, even while the harder autonomy layer remains unproven. That’s a calculated bet on a trajectory, not a blind one.

This is also where the 5% IT budget figure from the Canary survey deserves a second look. Five percent isn’t a moonshot allocation. It’s a measured, proportionate bet, sized to the part of the technology that’s already delivering value, guest communications and reporting assistance, rather than a wager on the autonomous layer that isn’t ready yet. Hotels aren’t betting the operation on unproven AI. They’re funding the proven slice generously while keeping the unproven slice on a shorter leash.

The NYU report itself points to where the gap is narrowing fastest: mid-sized hotel chains. Large enough to invest in specialist systems and staff, small enough to avoid the integration complexity slowing down bigger chains, mid-sized operators reported the strongest cross-functional alignment and the highest rate of meaningful AI-driven reductions in manual work. Scale, in this case, isn’t the advantage. The right scale is.

For hotels weighing whether to invest now or wait for a clearer ROI case, the honest answer sitting in this data is that waiting has a cost too. The properties currently building AI governance, staff training, and system integration, even without a fully proven payoff yet, are the ones positioned to move fastest once autonomy and trust close the remaining gap. The ones waiting for certainty are choosing to compete on last decade’s technology curve instead.

Where to Keep Following This Kind of Research

For hotel professionals who want research this specific, not just headline adoption percentages, a few sources consistently deliver it. Skift, founded in 2012 by Rafat Ali, produces original research on the travel and hospitality industry through its Skift Research division. Revfine, active for 8 years, publishes exclusively educational content on hotel technology and revenue management, marketing and operations, including its AI agents for hotels coverage. Hospitality Net, founded in 1994 in Maastricht, is the leading independent B2B portal for hotel professionals worldwide. PhocusWire, powered by Phocuswright’s travel research authority, delivers daily news and analysis on hotel technology and distribution.

The AI investment gap in hospitality isn’t a story about hype outrunning substance. It’s a story about a technology curve that rewards the hotels willing to move before every number is proven, the same way it rewarded early movers on distribution and revenue management before them. The full ROI case will eventually exist, in a report much like this one, a year or two from now. The hotels that waited for it will still be reading about it after the ones that moved first have already put it to work.

Disclaimer: This article is for informational purposes only and does not constitute business, financial, or technology advice. AI costs, benefits, performance, and ROI may vary depending on the hotel and its specific circumstances.