National Restaurant Show 2026 Recap: AI Essentials for Operators
Inside the AI Essentials for Operators workshop at the 2026 National Restaurant Show — practical use cases for menu profitability, menu engineering matrices like Stars and Plow Horses, and why Square's Claude connector is a real advantage for operators.
Published May 22, 2026 by BridgeWave Team
The 2026 National Restaurant Association Show in Chicago made one thing unmistakably clear: AI is no longer a side conversation in foodservice technology. It is being embedded into nearly every layer of restaurant operations by leading tech companies, from front-of-house guest experience and back-of-house production to reporting, inventory, scheduling, and finance.
BridgeWave was on the floor this year, and the most useful session we attended was a hands-on workshop titled "AI Essentials for Operators." What made it stand out was that it wasn't about a specific platform or a future roadmap. It was about practical use cases operators can put to work today, regardless of what POS, accounting, or inventory system they're currently running.
AI Is Being Embedded Across the Entire Operation
The vendors and integrators presenting at the show were aligned on a common theme. AI is showing up in:
- Front of house: conversational ordering, AI voice for phone orders, personalized recommendations, and guest sentiment analysis from reviews.
- Back of house: prep forecasting, waste tracking, automated line checks, and recipe-level cost monitoring.
- Reporting and finance: natural-language analytics, anomaly detection on labor and cost lines, and automated period-end summaries.
- Inventory and supply: invoice ingestion, automated price-change alerts from suppliers, and par-level recommendations.
The common thread is that operators no longer have to wait for their POS or accounting vendor to build a feature. With the right setup, an off-the-shelf AI model can do a lot of this work on top of the data you already have.
The Most Impactful Use Case: Real-Time Menu Profitability
The single most useful exercise from the workshop was building a real-time profitability model on top of the data every operator already has sitting in spreadsheets and PDFs.
The recipe was straightforward. Take three sources of data and load them into a single AI model. The session used Anthropic's Claude, which was the recommended model for the workshop:
- Your ingredient cost list from your food and beverage suppliers (typically a price sheet or invoice export).
- Your recipe list for each menu item, including quantities of each ingredient.
- Your menu and current menu prices.
Once that's in, the model can calculate plate cost, food cost percentage, and contribution margin for every menu item. Ask it a question in plain English and it returns a profitability model. Update a single supplier price and the model recalculates everything affected.
Layer In Sales Data and You Get Menu Engineering on Demand
The exercise gets more powerful when you add sales reports. Upload a sales mix export from your POS alongside the cost and recipe data, and the model can produce a full menu engineering matrix without you building a single spreadsheet.
Operators in the room were generating charts in real time for the classic four quadrants:
- Stars: high popularity, high profitability — protect and promote these.
- Plow Horses: high popularity, low profitability — candidates for re-engineering, repricing, or recipe changes.
- Puzzles: low popularity, high profitability — worth promoting, repositioning on the menu, or retraining staff to recommend.
- Dogs: low popularity, low profitability — strong candidates to cut.
From there, you can get as granular as you want. Filter by daypart, by station, by server, by location. Customize the analysis depending on what you're trying to decide — whether that's a menu refresh, a price adjustment, or a conversation with a struggling kitchen.
You can also push the model further by asking it to benchmark your prices against competitors in your local neighborhood, pulling in publicly available menus and pricing data to see where you sit in the market before you change anything.
Why Square's Claude Integration Is Worth Paying Attention To
One of the most interesting developments coming out of the show, and one that's directly relevant to BridgeWave partners, is that Square is currently the only POS we're aware of with an active integration to Anthropic's Claude model on their connectors marketplace.
That matters because it changes the workflow from a manual export-and-upload exercise into something that can run live against your sales data. Instead of pulling a sales mix report at the end of the week and pasting it into a chat window, the integration lets the model query directly against the POS data already flowing through Square.
What BridgeWave Can Build On Top of This
Pairing the Claude integration on Square's connector marketplace with a well-maintained recipe library and current supplier cost lists opens up something restaurants have wanted for years: a live profitability dashboard that updates with every order.
BridgeWave has the capability to build this for operators running on Square, as long as two things stay disciplined on the operator's side:
- Recipes remain consistent — what the kitchen actually makes matches what's recorded in the recipe library.
- Ingredient cost lists are properly updated per order from your food and beverage suppliers, so the model is always working from current pricing rather than last quarter's numbers.
If those two pieces are in place, the dashboard can show you real plate cost, real contribution margin, and real menu mix profitability in something close to real time. Decisions about pricing, promotions, and which items to keep on the menu stop being quarterly conversations and start being weekly ones.
The Takeaway for Operators
You don't need a new POS, a new accounting platform, or a custom-built AI tool to start using this. If you have your recipes, your supplier prices, and your sales reports, you can begin running these analyses this week with a single AI model. The operators who get ahead are the ones who treat this as a recurring operational discipline rather than a one-time project.
And if you're already on Square — or considering it — the Claude connector opens up a level of automation that very few other POS ecosystems can match today. That's an advantage worth understanding before your next technology decision.
Where BridgeWave Fits In
If you'd like help setting up a profitability model on top of your existing data, evaluating whether Square's Claude integration fits your operation, or scoping a live profitability dashboard for your restaurant group, that's the kind of work we do every day. We help operators turn the tools available to them today into something that actually changes how they run the business.