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Clean Data and Good Governance: The Real Foundation for Using Gen AI in Hospitality

Overall, there is no difference between preparing a dataset for AI and preparing a dataset for the myriads of other tech tools and business uses. By AI here, we mean Generative (Gen) AI-next-best-word, probability & correlation-based tools. Traditional analytical tools need normalised data (third normal form etc.) using Structured Query Language (SQL) with potential ambiguities removed in the design. Gen AI is useful to analyse text documents which are, by definition, unstructured, but it still acts as a glorified "word cloud" linking items together by frequency and probability. The main hospitality systems - PMS, POS, Spa, RMS, CRS, CRM - were built on normalized databases precisely to prevent mismatches, duplication, and gaps. Even then, duplicate guest profiles remain common, eg when a frequent guest changes email or surname. The better PMSes use fuzzy matching to ease de-duplication, but this remains a governance issue.

The Data Challenge: No Shortcuts to Quality or Value

It so happens I have a deep background on this topic. Over almost a decade, I deployed enterprise-level customer data consolidation for many of the world's leading luxury brands. In this capacity, developing the methodology and guiding execution of this specific desired outcome scores of times. The process always begins with the standardization of data and the rollout of those standards, followed by the cleanup of information sets once the standards are in place. Only after that point is true consolidation a reality.

Why Independent Hoteliers Must Connect PMS, CRS, and CRM to Unlock the Power of AI-Driven Personalisation

I believe priority #1 for independent hoteliers, midsize and smaller hotel brands is to create true two-way APIs among three crucial technology pieces: PMS-CRS-CRM. This is the only way to prepare the property for the agentic AI, expected to take over hotel bookings, guest relationships and personalization over the next years.

AI in Hospitality: Stop Counting Use Cases and Start Building Clean Data Foundations

I’ve probably been asked about a hundred times in the last two years to list the “main” use cases of AI in our industry. And while I understand what drives this request (we’re all just trying to wrap our heads around AI while drinking from the firehose of unlimited possibilities it presents), I’m not a big fan of boxing people in with a static list of examples.

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Centralised Guest Profiles: Powering Hospitality Through People, Not Just Technology

Having spent over 25 years at the intersection of hospitality operations and technology—most recently as Founder of EIP MGT GmbH, a vendor-neutral consultancy—I have seen the conversation around guest data shift from “what can we collect?” to “how do we use it to create real value?” The promise of a centralised, real-time guest profile is compelling, but only if it is leveraged to enhance—not replace—the human touch that defines our industry.

Why the hub-and-spoke model is the future of the hotel tech stack?

In the past, legacy technologies in hospitality used to be closed systems, reluctant to open up to third-party integrations, applications and solutions. This type of technology prevented property and its guests from adopting some very innovative and much-needed applications and services.

Will AI Make Hotel Websites Obsolete? Not Quite, but...

In my writings over the past decade, I have frequently returned to the notion that artificial intelligence is not merely an additional layer in the technological stack, but rather a reconfiguration of the Internet's ontological architecture. It redefines not only how we book, but also how we come to know, how we choose, and ultimately how we experience. AI is not simply the new interface, it is the new epistemology.

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