- How are restaurants actually using AI in 2026?
- The Most Popular Restaurant AI Question Isn’t About AI
- 1. “How Did We Actually Do Today?” — Sales and Revenue
- 2. “What Should Stay on the Menu?” — Menu and Inventory
- 3. “Who Should We Bring Back?” — Guests and Marketing
- 4. “What Am I Missing?” — Operations and Reporting
- The Bigger Shift: Restaurants Don’t Need More Data — They Need Better Answers
- Generic AI vs. AI That Knows Your Restaurant
- AI Should Remove Work, Not Add Another Dashboard
- What’s Next: From “Tell Me” to “Do It”
- What Restaurant Owners Are Asking AI About
- Frequently Asked Questions
- More Helpful Reads
When people hear “AI in restaurants,” they picture robot kitchens, automated drive-thrus, and machines replacing the people behind the counter. It makes for a good headline. It is also almost nothing like what is happening in real restaurants right now.
In the first quarter of 2026, the single most-used AI request across a very large group of restaurants was, in plain terms, this: tell me what happened in my restaurant today, quickly. Not a robot flipping burgers. A tired operator asking a good question and getting an answer in seconds instead of digging through five reports.
That tells you more about where restaurant AI stands in 2026 than any robotics demo. Owners have always had questions about their own business. What is changing is that they can increasingly just ask their technology and get a straight answer back.
How are restaurants actually using AI in 2026?
Restaurant owners are primarily using AI to understand sales, manage menus and inventory, improve marketing, and simplify reporting. In Q1 2026, Toast found that 47% of restaurants using its AI assistant asked about sales and revenue, 34% about menus and inventory, 32% about guests and marketing, and 29% about operations and reporting.
That is the story in one paragraph: the most useful restaurant AI is becoming less futuristic and more practical.
The Most Popular Restaurant AI Question Isn’t About AI
Toast analyzed anonymized activity from more than 125,000 U.S. restaurant locations using Toast IQ between January and March 2026, with more than 179,000 users interacting over the quarter. Because that is such a large sample of real restaurant-AI conversations, it gives an unusually honest look at what operators actually ask, rather than what technology companies assume they should ask.
The most-used individual prompt was not clever or experimental. Roughly 15% of restaurants using the AI assistant asked it for a short, easy-to-read daily briefing on their business.
Think about what that request really is. Owners do not want another dashboard to log into. They want answers to a few ordinary questions: What changed? Is anything unusual? What needs my attention? That information usually lives in separate places — the POS report, the online ordering system, three delivery platforms, a spreadsheet — and someone still has to pull it together and interpret it. A conversational interface quietly changes the relationship from dashboard, then interpretation, then decision to question, then answer, then decision.
Why are restaurant owners asking AI for daily business briefings?
Restaurant operators generate large amounts of sales, menu, labor, and customer data but have very little time to analyze it. A daily AI briefing can summarize the important changes and surface what deserves attention, without an owner working through multiple reports before the lunch rush starts.
1. “How Did We Actually Do Today?” — Sales and Revenue
Sales and revenue was the largest category at 47% — the first thing most owners want to know and the last thing they have time to calculate by hand. The questions are not complicated AI questions. They are normal management questions that used to require pulling and reading a report:
- How much did we sell today, and how does that compare with last Thursday?
- Which channel produced the most revenue, and were my highest-selling items?
- Was lunch or dinner stronger, and did average order value change?
- Did sales fall even though order volume went up?
That last one matters. “More orders, less money” is exactly the pattern that hides inside a busy week and quietly costs margin. Being able to ask about it directly, grounded in your own numbers, is the point.
How can restaurants use AI to analyze sales?
AI can help restaurant operators summarize sales, compare periods, spot unusual changes, and break revenue down by item, location, or order channel. The most useful systems analyze the restaurant’s actual data rather than offering generic business advice, so the answers reflect what really happened.
2. “What Should Stay on the Menu?” — Menu and Inventory
Menu and inventory came second at 34%, and a further 26% of restaurants started conversations specifically about menu optimization. Operators are asking:
- What are my best-selling dishes, and which items aren’t selling?
- What should I 86 today?
- Which items get ordered together, and which modifier is most popular?
- Which items deserve more visibility on the menu?
One honest limit is worth stating plainly: AI cannot give you a useful margin recommendation from sales data alone if it does not know your ingredient costs. It can tell you what is selling; it cannot tell you what is profitable unless that data is connected. Keep that in mind before you cut a dish that sells slowly but earns well.
Can AI help restaurants optimize their menus?
Yes. When connected to accurate restaurant data, AI can identify best sellers, slow-moving items, ordering patterns, and menu trends. Operators should still combine those insights with food cost, preparation complexity, and their own knowledge of the room before changing the menu.
3. “Who Should We Bring Back?” — Guests and Marketing
Guests and marketing accounted for 32% of AI conversations. This is where restaurant AI gets more interesting than “write me an Instagram caption.” Operators are asking:
- Which customers haven’t ordered recently?
- What should we promote this weekend, and to whom?
- Which segment is most likely to come back, and what did they respond to last month?
Notice the shift. The weaker use of AI is generating generic promotional copy. The stronger use is answering which customers should I talk to, about what, and why. One is a writing assistant; the other helps you decide where to spend limited marketing attention.
How can restaurants use AI for marketing?
Restaurants can use AI to analyze customer behavior, identify useful audience segments, suggest promotions, and assist with email or SMS campaigns. AI becomes far more valuable when its recommendations are based on real order history rather than generic ideas that could apply to any business.
4. “What Am I Missing?” — Operations and Reporting
Operations and reporting made up 29% of conversations. This category speaks most directly to the overwhelmed operator. The questions sound like the running to-do list in an owner’s head:
- Which hours were unexpectedly slow, and where did orders come from today?
- What needs attention before tomorrow?
- Did one location behave differently from the others?
- What happened during yesterday’s rush?
The value here is not “AI analytics” as a feature. It is simpler and more human: I don’t have to spend 45 minutes at the end of the night figuring out what happened. For someone already working too many hours, getting that time back is the benefit that matters.
The Bigger Shift: Restaurants Don’t Need More Data — They Need Better Answers
Here is the strongest point in all of this. Restaurants are not short on data. They are drowning in it: sales, orders, menu performance, customer behavior, delivery metrics, reviews, payments, marketing activity. The problem is rarely that the information does not exist. It is that the information lives in different systems, and someone still has to interpret it.
Orders.co’s own market research keeps surfacing the same two complaints from independent operators: fragmented systems and operational overload. One tool for ordering, another for menus, another for reporting, none of them talking to each other. AI does not fix that on its own, but it changes what “good” looks like — the goal stops being a prettier report and starts being a faster, clearer answer.
Why is connected restaurant data important for AI?
AI can only analyze the information it can reach. When sales, orders, menus, and customer data are scattered across disconnected systems, an AI tool may see only part of the business. More connected data gives operators a more complete and reliable foundation for any analysis worth acting on.
Generic AI vs. AI That Knows Your Restaurant
It helps to separate two different things that both get called “restaurant AI.”
Generic AI, like a general chatbot, is good at brainstorming promotions, rewriting menu descriptions, drafting emails, and generating ideas. That is real, useful work, and any owner can start there today. Restaurant-data-connected AI can answer a different class of question: What happened to my sales yesterday? Which menu item declined this month? Which customers haven’t returned? Which channels are growing?
Toast leans on the value of AI connected to sales, labor, menu, guest, and operational data, and Square’s restaurant AI similarly lets operators ask natural-language questions about their own performance. Either way the takeaway is the same: a smarter chatbot is useful, but a system that actually understands your restaurant is far more useful.
AI Should Remove Work, Not Add Another Dashboard
This is the practical test to apply to any restaurant AI tool: does it remove work, or just add one more screen to check?
If an owner has to copy numbers out of five dashboards before asking AI what they mean, very little has actually been automated — the manual work simply moved to a different step. That is why the foundation for useful restaurant AI is not adding one more AI app on top of the pile. It is reducing fragmentation first, so the data is accessible and organized before you ask anything of it.
This is where Orders.co fits, and it is worth being clear about how. The platform brings orders from the POS, restaurant website, kiosk, and integrated third-party providers into one workflow, alongside centralized menu management, restaurant reporting tools, and restaurant marketing automation. Before AI can help you understand your restaurant, your restaurant’s information has to be reachable and organized in the first place.
What’s Next: From “Tell Me” to “Do It”
It helps to think about restaurant AI in three stages. Generative AI writes the promotion for Friday — useful, and widely available now. Analytical AI tells you that Friday dinner traffic has declined 8% over four weeks; this is where the Toast data shows most operators living today. Agentic AI goes further: “Create a Friday campaign for the customer segment most likely to respond.” Restaurant technology companies are beginning to introduce agents that assist with real operational tasks, from marketing to scheduling, and Square has extended from conversational analysis toward a more proactive business agent that surfaces insights and automates routine work.
What Restaurant Owners Are Asking AI About
| Topic | Share of restaurants in Toast dataset |
| Sales and revenue | 47% |
| Menu and inventory | 34% |
| Guests and marketing | 32% |
| Operations and reporting | 29% |
| Menu optimization opportunities | 26% |
| Labor costs and efficiency | 13% |
Source: anonymized activity from more than 125,000 U.S. restaurant locations using Toast IQ in Q1 2026. These figures represent Toast’s dataset, not every restaurant in the United States.
Frequently Asked Questions
AI for restaurants refers to software that uses artificial intelligence to analyze information, automate repetitive tasks, or help operators make decisions. Restaurant AI can be used for sales reporting, menu analysis, marketing, forecasting, customer engagement, inventory, and other operational tasks.
Restaurants are using AI most heavily for everyday business decisions. Toast’s Q1 2026 analysis found that 47% of restaurants using its AI assistant asked about sales and revenue, followed by menu and inventory at 34%, guests and marketing at 32%, and operations and reporting at 29%.
In Toast’s Q1 2026 dataset, sales and revenue was the most common operator-initiated AI topic. The single most-used prompt asked AI to create a short daily restaurant briefing, which suggests operators particularly value fast summaries of business performance over more experimental uses.
A small restaurant can start with practical tasks such as summarizing sales, brainstorming promotions, analyzing menu performance, drafting customer messages, and spotting patterns in its data. Start with one repetitive problem you already have rather than adopting AI simply because it is new.
AI can help operators identify sales patterns, popular items, customer segments, and promotional opportunities, but it does not automatically increase revenue. Its value comes from helping owners recognize opportunities and make decisions faster using reliable business data, not from the technology itself.
Yes. AI can help analyze menu demand, identify popular and underperforming items, suggest descriptions, and surface patterns in ordering behavior. Operators should still weigh food costs, preparation requirements, and customer expectations before making menu changes.
Yes. AI can help restaurants create promotions, segment customers, draft SMS or email campaigns, and identify customers who may be likely to return. Marketing becomes more useful when the AI has access to real customer and ordering data rather than relying only on generic prompts.
