Part 4: Let’s pull back the curtain on the buzzword of the decade - AI!
Throughout my years in the hospitality industry, I have been involved in a multitude of RFIs, RFPs, and other processes for selecting a new hotel management system, commonly referred to in the hospitality industry as a Property Management System (PMS).
During this time, it has been impossible not to notice some questions that all too often do not receive the attention they deserve, and several that are brought to the table unnecessarily or even far too late, when crucial decisions have already been made.
A Hotelier's Guide to Spotting the Waffle
If you’ve walked through a hospitality trade show recently, you’ve probably been bombarded. Every stand, every salesperson, every glossy brochure seems to be shouting about their "AI-Powered," "Intelligent," "Cognitive," or "Smart" platform. It seems every new bit of software has suddenly developed a digital brain worthy of a sci-fi film.
But here’s the rub: if you ask for the details, the conversation often gets a bit... fuzzy. The grand claims of artificial intelligence shrink into vague promises of "efficiency" and "optimisation." You're left wondering if you're about to invest in the future of hospitality, or just a fancy calculator with a good marketing team.
Following on from our series on asking the right questions of your tech providers, let's pull back the curtain on the buzzword of the decade. It's time to arm you with a healthy dose of scepticism and the right questions to ask, so you can tell the genuine innovation from the glorious, gilt-edged waffle.
HAL 9000 vs. The Clever Spreadsheet
First things first, let's clear up what most tech vendors mean when they say "AI."
What they want you to picture is something called Artificial General Intelligence (AGI). This is the stuff of Hollywood: a self-aware, thinking, reasoning mind like HAL 9000 in 2001: A Space Odyssey or Second Officer Data from Star Trek. An AGI hotel manager would anticipate a guest's desire for a late checkout based on their flight schedule, their mood at breakfast, a smear of lipstick on the collar, and the weather forecast, all without being asked. Spoiler alert: this technology does not really exist in any hotel tech platform. (Yet.)
What they almost always actually mean is Machine Learning (ML). Machine Learning is a brilliant and genuinely useful subset of AI, but it is not a thinking brain. It’s about teaching a computer to recognise patterns in vast amounts of data and then make predictions or decisions based on those patterns.
Think of it this way:
- AGI is the brilliant, intuitive hotel concierge who knows what you want before you do.
- ML is the incredibly diligent analyst who has studied the last five years of booking data and can tell you with 85% confidence that you should raise your rates for the second Tuesday in October because of a recurring local conference.
The Buzzword Bingo Hall of Shame
The path to a good tech decision is littered with buzzwords designed to sound impressive whilst meaning very little. Here are a few favourites to watch out for.
- "AI-Powered": This is the king of vague terms. A system that sends an automated email when a room is booked could be described by a particularly cheeky marketing department as "AI-powered." It’s technically an automated process, right?
- Your Defence: Ask, "Powered in what way? Which specific process uses a machine learning model, and what does it do?"
- "Intelligent Automation": This sounds better than "Plain Old Automation." Often, it refers to simple "if-this-then-that" rules. For example, "if a guest books a family room, then automatically send them information about our kids' club." That's not intelligence; that's a pre-programmed rule. It’s useful, but it isn't HAL 9000 managing your guest communications.
- Your Defence: Ask, "How does this 'intelligent' automation differ from a standard rules-based workflow? Does it learn or adapt over time?"
- "Predictive Analytics": This is a legitimate function of Machine Learning, but it's not Harry Potter. A good predictive model can be a game-changer for revenue management or marketing. A bad one is worse than useless—it’s misleading. Talking to a chatbot that can only understand three keywords is not a conversation with a digital brain; it's a frustrating game of guess the password.
- Your Defence: Ask, "What data is used for these predictions? Can you show me the model's historical accuracy? What is the margin for error?"
Your Anti-Hype Toolkit: Three Questions to Cut Through the Noise
When you're sat in a demo and the "AI" word is dropped, take a deep breath and deploy these questions. A good partner will have solid answers. A waffler will start to squirm.
1. "Can you show me exactly where and how your platform uses machine learning, and what data it uses?"This forces them to be specific. A vague answer like, "The AI optimises the entire guest journey" is a red flag. A great answer sounds like this: "Our dynamic pricing module uses a regression model that analyses your historical occupancy, booking pace, competitor rates we scrape, and even local event data. It then suggests daily rate adjustments. You can see the key drivers for its suggestions right here on the dashboard."
2. "What specific, measurable business outcome will this feature deliver for my hotel?"
You’re not buying technology for the sake of it; you’re buying it to solve a problem or achieve a goal. Connect the feature to the money. A bad answer is, "It will make your operations smarter." A good answer is, "Our ML-driven segmentation tool analyses guest spending history to identify high-value patrons for targeted marketing. Hotels using it have seen an average 15% increase in repeat bookings from that segment."
3. "Who owns the data, the model, and the insights?"
This is the big one. The machine learning model needs data to learn. Is it using your hotel's precious data? Is that data being pooled with data from other hotels (including your competitors) to train a central model? If your data helps their model become smarter, who benefits from that? Do you own the insights and pricing strategies it develops for your property, or are you just "renting" them? This is a critical question of digital ownership that can have a long-term implication for your business.
The Intelligent Choice
True artificial intelligence may still be the stuff of science fiction, but applied Machine Learning IS a real and powerful force for change in the hotel industry. It can help you optimise revenue, personalise guest experiences, and streamline operations in ways that were previously impossible.
My goal is NOT to dismiss AI, but to demand clarity. Don't be dazzled by the buzzwords. Be the calm, collected hotelier who asks simple, direct questions and insists on concrete answers.
The most intelligent thing in any hotel isn't the software—it's the person choosing it. Make sure YOUR choice is a properly informed one.
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On a personal note, I would add that Clock Hospitality Cloud naturally includes several functions and automations built on Machine Learning. A prime example is our current work on recognising repeat guests and automatically deduplicating their profiles.
To practise what we preach and be specific: our model learns from historical data, analysing various signals such as a guest's city or phone number. This allows the system to identify a returning guest, regardless of how their name is spelled and even if certain information is missing entirely.
Please feel free to get in touch for more information.
Yours truly,
Kim
