Restaurant kiosks have spent years making ordering more efficient by turning a menu into a touchscreen. Square now appears to be pushing the format toward something more conversational.
Square’s first dedicated kiosk hardware with an AI ordering assistant uses a 21.5-inch display and lets diners ask questions such as which options are vegetarian or what is available for under $10. The system is trained on each restaurant’s menu, including popular items and suggested pairings.
That changes the kiosk from a digital menu into a lightweight ordering guide. The important move is not simply that Square has added AI. It is that the assistant is being placed at the point where a customer is deciding what to buy.
Square is making the menu easier to navigate
Square’s existing kiosk system already supports self-serve ordering, contactless and chip payments, menu updates, order notifications, loyalty connections, and Smart Upsells. Its official Square Kiosk product page positions the hardware as part of a wider restaurant system that connects the customer-facing screen with the point of sale.
The AI layer adds a different kind of utility. Instead of asking diners to understand the restaurant’s categories, modifiers, and product language, it gives them a more natural way into the menu. A guest can start with a preference, a dietary question, or a price limit rather than knowing exactly what item to select.
That matters because restaurant menus are often built around the operator’s logic, not the customer’s. Categories may make sense internally while leaving first-time visitors unsure where to begin. A conversational interface can translate between the two.
The bigger shift is from ordering automation to decision support
Traditional kiosks automate the transaction. Square’s reported assistant is designed to influence the decision before the transaction happens. It can surface popular items, explain options, and potentially steer diners toward combinations that reflect how a restaurant wants its menu to be experienced.
That puts more responsibility on the quality of the underlying menu data. If the system is trained on accurate item descriptions, availability, dietary information, and pairings, it can reduce friction. If those inputs are incomplete or stale, the conversational layer risks making the menu feel more helpful while introducing a new route to confusion.
The commercial implication is equally clear. Square is not treating AI as a separate destination for restaurant operators. It is placing it inside the existing ordering flow, alongside payments, customer data, upsells, and kitchen operations. For restaurants, the opportunity is not to offer an impressive chatbot. It is to make the menu easier to understand while preserving the operator’s control over what gets recommended.
The strategic consequence is that self-service ordering is becoming less about removing people from the interaction and more about redesigning how customers make choices. The best kiosk may no longer be the one with the fewest taps. It may be the one that understands what the diner is trying to ask.