KHN's AI special says it too, start small and start with your own data

This summer, Royal Dutch Hospitality (KHN) published an AI special: practical tips for putting AI to work in your venue. We read it cover to cover. It is level-headed, practical and free of hype, and its through line lands exactly where our own thinking sits.

The heart of the special is not an impressive tool. It is three plain pieces of advice: start small, look at the work behind the scenes, and stay in charge yourself. All three are right, and all three say something about where AI does and does not belong in hospitality.

Start small, with the work that eats time

The first piece of advice is the easiest to ignore and the most important to follow: pick one task. Not a strategy, not a transformation, one task that keeps coming back or takes more time than it should. Test, learn, adjust.

The special puts it sharply: do not go looking for an AI tool, first look at where you lose time or leave opportunities on the table. That is a reversal worth remembering. The question is not "what can AI do", the question is "where does it get stuck for me".

And you usually already know. The colleague explaining the allergen sheet for the tenth time. The recipe being worked out again because the regular cook is off. The shift handed over half-finished because it was busy. These are not big problems, they are small leaks, every shift again. That is exactly where it should start.

The value is in data you already have

The second piece of advice is about data, and here too the special is refreshingly plain. Good insight does not begin with a new system, it begins with the data already sitting in your venue. Your till, your purchasing, your reservations, your rosters. Every venue already knows a great deal, that knowledge is just scattered across heads, folders and separate systems.

That is the real work before AI can mean anything: getting that knowledge into one place. Not to make things more complicated, but to give you an overview. As long as the knowledge of the house lives in loose corners, no clever tool can do anything useful with it. Once it sits together, AI can show you where your margin leaks away, or which dish barely earns anything at current purchase prices. Work that would otherwise cost you half a Sunday with a spreadsheet, if you ever get to it at all.

The operator stays in charge

The third part of the special may be the most important, and it is the part most AI stories skip. KHN is honest about the risks: privacy, reliability, and the danger of leaning too heavily on technology you do not control yourself. Check what AI produces before you use it. Do not drop confidential information into a tool. The operator decides, AI does the groundwork.

That is not a brake on AI, it is the condition for trusting it. Your data should be yours. What goes public is your call. And the knowledge of your venue should not disappear into a system you can no longer reach. AI only becomes useful when you stay at the wheel.

Where moonies stands

moonies is built on that side on purpose. It is the back office of the venue, the work that happens out of sight to keep the place running. Recipes and prep that hold up even when the regular cook is off. The knowledge of the house in one findable place instead of in one person's head. A handover that genuinely helps the next shift.

That is exactly the "start small, start with your own data" the special recommends, only as a product. And once that work sits in one place, AI can really do something with it, in the background, without the guest noticing a thing. You stay in charge, because it is your venue and your data.

We wrote earlier about why the best AI in your venue is the AI your guests never see, and how recipe software compares to a spreadsheet as a first step with your own data.

If you have not read KHN's AI special yet, do. It is a good, honest piece. And when you are ready for that one first step behind the scenes, take a look in the kitchen or read how we look at the venue.