Hospitality Has an AI Opportunity — But a Data Problem

Hospitality is talking more and more about AI, but in practice the industry still feels behind.

I think one of the main reasons is simple: most businesses do not have the data foundations in place for AI to create real value. There is a difference between people using tools like ChatGPT directly, and hospitality businesses actually adopting AI in a deeper operational way.

That second part is much harder.

Why? Because hospitality data is usually spread across multiple systems: PMS, POS, CRM, finance, staffing, guest communication, reviews, marketing platforms, and often a lot of manual spreadsheet work too. When the underlying structure is fragmented, AI adoption stays fragmented as well.

So the bottleneck is often not “AI” itself.

The bottleneck is whether the business is organised well enough, from a data point of view, for AI, analytics, and automation to be useful in the first place.

This is also the thinking behind a project I’m working on at the moment: exploring how hospitality businesses can become more AI-ready by structuring scattered data more clearly across functions.

I’m curious how others see this.

Is hospitality behind on AI mainly because of culture and mindset, or because the systems and data underneath are still too messy?

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