When AI Becomes the New Front Door to Commerce ⋅ Maria Zhang

An office manager asks her AI assistant: “Find lunch for 25 people tomorrow. Keep it under $500, include five vegetarian meals, and have it delivered to our office by noon.”

Her assistant narrows the options, checks the details, and helps place the order. By the time the restaurant hears from this customer, much of the decision may already be made.

Parts of that experience are already here. In August, Google announced food ordering in Ask Maps with partners including Toast and Square. Customers can describe what they want, select a restaurant, and have a dish added to their cart for review and checkout.

In my earlier article on the AI front door, we explored how restaurants can receive requests from guests and their AI assistants and connect them to the right systems or people. Now comes the commercial question: how does a restaurant earn the recommendation, win a profitable order, and give that customer a reason to return?

From attention to recommendation

Restaurant marketing has long worked to earn a guest’s attention: show up in search, share an appealing dish, give someone a reason to visit. AI adds a new audience to win over. A digital assistant may evaluate your restaurant before the customer ever sees your name.

Reuters recently explored this shift through Amazon and Walmart’s advertising businesses. As shoppers delegate more decisions to AI, brands are preparing product information that agents can evaluate. The same reporting describes advertising moving into AI assistants, so operators should expect paid promotion to remain part of the picture.

For restaurants, we believe clear operating information is becoming a core part of marketing. Take that office lunch. An assistant needs to establish what feeds 25 people, which meals are vegetarian, whether the delivery address is covered, and whether the total, including fees and taxes, fits the budget. And it needs confidence that you can deliver tomorrow.

Alongside your photography and brand story, make those details easy to find and keep them current for each location. Publish catering portions, prices, minimums, and lead times. Give customers a clear way to order or get an answer.

Accurate information won’t guarantee a recommendation, but it gives an assistant what it needs to see when your restaurant fits the occasion.

A recommendation has to become an order

Getting mentioned by AI can feel like a marketing win. What matters is how much of that attention turns into revenue.

An October working paper by Kaiser and Schulze offers an early caution. In its US paid advertising comparison across 102 websites, paid ChatGPT visits generated $0.89 in revenue per session versus $2.45 for paid Google Search visits. Those findings concern paid ad traffic; they do not establish how restaurant recommendations or purchases made by AI agents will perform.

For operators, the real test comes after the recommendation.

Suppose the office manager chooses your restaurant. She still needs to confirm quantities, delivery timing, and the final price. If the ordering page cannot handle her request, or her follow-up call goes unanswered during the lunch rush, the sale is still at risk.

Closing that sale requires the working connections we described in our earlier article: accurate information, supported ordering paths, and a manager who can resolve exceptions.

Track completed orders, the margin after channel costs, and repeat purchases. For catering, follow the inquiry through confirmation and fulfillment. That is how you learn whether a new source of demand is worth growing.

Keep the customer relationship

New orders are always welcome, especially once the kitchen is staffed and the food is prepped. Third-party platforms can introduce a restaurant to people it would struggle to reach on its own.

But the terms of that introduction matter. If a platform handles discovery, checkout, and every follow-up, the restaurant may receive an order without learning much about the person behind it.

Was this a one-time celebration or a weekly office lunch? What mattered most to the buyer? With their permission, can you follow up, remember their preferences, and make the next order easier?

That’s the value of a direct customer relationship: it lets a restaurant serve someone better over time and earn their repeat business.

AI does not dictate a single model for that relationship. Walmart’s October announcement, for example, describes connecting outside agents to customers’ Walmart accounts, with purchase approvals and spending controls. It suggests a useful principle for restaurants: customers can choose an AI assistant while maintaining a relationship with the business fulfilling the purchase.

An order that begins with AI is not automatically a direct order. The route through checkout, the fees, and the customer information the restaurant receives determine what the restaurant gains. Use new channels to reach guests while continuing to invest in your own ordering experience and customer relationships.

Your restaurant needs a way to respond

This is where the AI front door I described becomes useful: a conversational entry point on a restaurant’s website that answers questions and routes requests to supported systems or the right person. It gives the restaurant a direct way to act on demand.

That’s what we’re building at Palona. Our ordering agents answer questions and send orders into supported POS systems. Our catering agents gather the requirements behind an event and bring the details to the restaurant’s team. Revenue Intelligence helps operators see where inquiries stall and where follow-up is needed.

As more consumer assistants connect with restaurant systems, this approach can extend across more channels. A customer’s assistant communicates what the guest needs, and the restaurant’s systems confirm what can be provided under the operator’s rules.

That future depends on reliable integrations and clear approvals. Today, operators can build the foundation by keeping their information accurate, answering inquiries promptly, and making direct ordering easy.

Make the next order easier

Start with the lunch request at the beginning of this article. Could a customer or their assistant find enough information to choose your restaurant? Could they complete the order? Would your team have the context and permission to serve them again?

These questions matter no matter how fast AI shopping grows. Answering them improves the experience for the guests trying to buy from you today.

AI may become the front door, but the meal and the service are still what bring a customer back. The strongest outcome is a guest who goes back to their assistant and says, “Order from the same restaurant as last week.”