Hospitality AI spending keeps climbing, but results aren't keeping pace with the investment. On August 25, 2026, from 15:30 to 16:30 CEST, Lighthouse is hosting a free online session to help hotel commercial teams build a practical framework for evaluating AI before budgets disappear.
The session targets two distinct audiences. Revenue Managers will learn to spot use cases that "give you back your mornings, and the ones that quietly create more work." Commercial Leaders will get answers to their board's AI questions, plus a plan for what to fund, what to cap, and where to start.
A framework before the pitch
Every AI vendor claims their product is faster, smarter, and cheaper. Without a framework, teams struggle to separate earning AI use cases from waste. The session will cover how to set cost limits before they're needed and how to make the build vs. buy call.
For those new to this territory, foundational guidance on evaluating AI tools is part of the broader discussion around AI for Hospitality & Events. That category covers the practical application of AI for professionals working in hotels, venues, and events.
Budget for judgment, not replacement
The webinar's central promise is an AI budget that "pays to amplify judgment instead of replacing it." Real examples and a live Q&A are included with registration. The event is organized by Lighthouse, formerly OTA Insight, a commercial platform providing market insights, business intelligence, and pricing tools for the travel and hospitality industry.
For commercial leaders, the financial stakes of large AI investments fall squarely under AI for Executives & Strategy - the budget decisions made now will determine whether AI tools become productivity assets or cost centers.
Why this matters for hospitality and events professionals
Hotel commercial teams face pressure from both directions. Sales and distribution leaders keep hearing that AI is essential, while finance teams want a return on every dollar spent. This session offers a rare middle path: a clear way to evaluate any AI pitch against real operational needs, set cost limits before vendors set them for you, and walk into the next budget meeting with defensible answers. The result should be a toolset that makes commercial judgment faster and better, not a collection of subscriptions that require more staff time to manage.
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