These are still relatively early days for artificial intelligence (AI) — and especially so in the restaurant industry. Yet momentum for the technology is building, with AI chatbots taking food orders, appliances responding to voice commands and virtual assistants drafting marketing copy. Indeed, restaurants stand to benefit from AI in fundamental aspects of their businesses. This article highlights pioneering and potential uses of AI as restaurant technology continues to evolve.
What Is AI in Restaurants?
AI is emerging in the restaurant industry with applications from front-of-house customer interactions to back-of-house kitchen operations and administration. AI is also indirectly affecting restaurants through connected industries, using pattern recognition and other advanced capabilities in widely adopted applications, such as voice assistants on smartphones, self-driving forklifts in factories and recommendation engines on websites
Adoption is coming about in three ways:
Many restaurant technology providers are adding AI in software upgrades to workhorse platforms, like point-of-sale (POS) and inventory management systems — particularly to mitigate food waste. For example, an advanced POS system can track a restaurant’s recent orders, analyze which items are frequently bought together and then suggest different pricing or combo offers to increase sales.
New AI-based products are coming to market, with highly publicized examples, including robotic cooks, dishwashers and servers.
AI innovators are partnering with existing technology vendors, using application programming interfaces (APIs) to integrate AI capabilities into widely used kitchen display systems, back-office customer relationship management (CRM) software and other restaurant IT stalwarts.
While the restaurant industry lags behind other sectors in AI adoption, it’s catching up. Across all industries, over 72% of organizations use AI in some form, according to McKinsey, a management consultancy. Some 47% of restaurants currently do so, with larger restaurant groups leading the field, according to the “2024 Restaurant Technology Outlook” report from Nation’s Restaurant News (NRN). Of those restaurants not currently using AI, 35% indicated that they would like to, and the recent surge in usage of popular generative AI chatbots, such as ChatGPT, is likely to accelerate growth.
The most popular restaurant applications in use, per the report, are (in descending order) loyalty programs/targeted marketing, sales and labor forecasting, labor management/scheduling, inventory management, POS, back-of-house/kitchen operations and employee safety/food safety.
Key Takeaways
- Big fast-food chains are leading the restaurant industry’s foray into using AI.
- Applications are growing, ranging from drive-through chatbots to back-of-house business systems.
- The new technology can help ease industry challenges, such as labor shortages and flat customer traffic.
AI in Restaurants Explained
Big restaurant chains have been touting their AI applications — even branding them — and their pilots and implementations are paving the technology’s way into the wider restaurant world. Among those in the vanguard:
- Wendy’s FreshAI: Following trials in Ohio, the fast-food chain said it is expanding its use of AI for drive-through ordering to increase service speed, accuracy and consistency, while keeping restaurant employees focused on preparing and completing orders. Generative AI chatbots deliver an 86% accuracy rate, company officials say, which accounts for nuances, such as customization requests, that trip up traditional rule-based chatbots. (Problematic orders may be escalated to employees.) Wendy’s has also predicted that it will use more AI in apps, kiosks and other channels.
- Yum! Brands’ SuperApp: This mobile app for restaurant managers in Yum’s Pizza Hut and KFC locations incorporates generative AI to ease access to day-to-day operational questions, such as temperature settings on ovens. But SuperApp is just one of the restaurant group’s 40 AI projects. Another is its platform for analyzing and optimizing the sequence of pizza orders based on delivery locations and traffic patterns.
- Starbucks’ Deep Brew AI: Starbucks uses this predictive AI platform to “hyper-personalize” marketing to customers based on past purchases, time of day, weather and other factors, and also to develop new products based on customer preferences. In addition, the chain’s AI uses include preventive maintenance of Internet of Things (IoT)–connected espresso machines.
Not all AI uses in restaurants have been well received by customers. One chain’s announcement of “variable pricing” was being decried for its similarity to airline surge pricing. Another major chain’s trial of robot servers and hosts fell flat and was discontinued. Yet, with ongoing AI experimentation, iteration and cost reductions, these and other AI innovations are expected to regroup and reemerge. AI is becoming more of a fixture in the restaurant industry every day.
Why Should Restaurants Implement AI?
When rolling out AI, big restaurant chains often take care to issue reassurances that the technology will not replace their employees. Labor is a key consideration, though, given today’s shortage of workers, significant turnover rates and historically low wages. Additional technology drivers include stiff competition, weak customer traffic and inflation in food prices, utility rates and other costs. And, in early 2024, the National Restaurant Association’s (NRA) Restaurant Performance Index showed ongoing deterioration in a composite of four industry indicators: same-store sales, traffic, labor and capital expenditures.
Big or small, all restaurants can take advantage of AI to reduce some of these challenges as the technology proves itself, comes down in price and becomes more widely available. A prime example is food waste management. One survey found that over half of U.S. restaurants throw out 100 to 500 pounds of food in a typical week. Experts say AI’s pattern recognition, prediction and machine-vision capabilities can address some of the main causes — such as demand fluctuations, overordering/spoilage, oversized portions and cooking errors — through advanced sales forecasting, real-time inventory management and controls on quality and portion size.
15 Ways to Use AI in Your Restaurant
AI innovations stole the spotlight at the NRA’s annual convention in 2024, both on the exhibition floor and in panel discussions, such as “The Journey of AI and Robotics in Enhancing Guest Experiences.” On display: an AI menu-building concept for chefs to create new recipes, a robot server that recognizes the menu items on its tray and announces them to diners, and an oven that responds to chefs’ voice commands or simply starts the appropriate cooking program by sensing which type of food is inserted. Other innovations at the show included some of the examples below.
Chatbots and Virtual Assistants
About half of restaurant customers prefer making reservations online or on a smartphone app, according to a 2024 global survey of restaurant owners. The integration of AI capabilities can augment reservation systems by providing 24/7 automated support through chatbots. These AI-powered chatbots can answer typed (and increasingly spoken) questions and make recommendations in more natural language. Other chatbots handle phone interactions in a similar way. In the background, meanwhile, reservation systems can optimize table management and feed into a restaurant’s POS or CRM system to streamline checkout or develop more strategic marketing.
In addition to facilitating reservations, chatbots are becoming increasingly prevalent for ordering online, by phone, at drive-throughs and at in-store kiosks, and chains are beginning to upgrade their voice capabilities. In addition to Wendy’s rollout in drive-throughs, described above, several other chains are starting to use voice-based AI in their drive-through lanes. Taco John’s, for example, announced plans to roll it out to its 350-plus franchises in 2024, after trial results showed that it led to faster service, increased order accuracy and resulted in more sales driven by automated upselling. Orders taken by the system show up directly on kitchen display screens to expedite preparation.
Voice-Activated Systems
Chatbots are not the only tool making use of voice-based AI. Voice-activated systems are poised to help restaurant staff improve food preparation and service. Chefs and kitchen staff literally have their hands full during busy shifts. But they can use voice activation to communicate more easily — and hands-free — with prep stations in the kitchen, inventory systems and front- and back-of-house, so they can check on orders or the availability of prepped items in the walk-in refrigerator. Chefs can also use voice-controlled appliances to set ovens or consult recipes using voice AI when they’re on the line.
Recommendation Engines
Recommendation engines have become commonplace online, in the form of tools that prompt consumers to add items to their purchases. To play on a well-known phrase, in the restaurant industry chatbots never forget to ask if you want fries with that.
Older recommendation engines in ordering systems are rules-based, with restaurant managers predefining upselling tactics by identifying foods and beverages that might pair well. Newer recommendation engines use predictive analytics that derive upselling possibilities based on customers’ past orders and other data. Advanced natural language processing skills also enable a customer and chatbot to discuss recommendations.
Customized Marketing
Digital marketing topped restaurateurs’ list of technology investment priorities for 2024, with 63% of survey respondents budgeting for it, according to the NRA’s most recent “Restaurant Technology Landscape” report. Digital marketing also dominated the list of current AI applications in the separate outlook report from NRN. Many of the restaurants expressed dissatisfaction with their digital marketing capabilities to date, including their inability to make use of all the customer data they have.
With its pattern recognition and predictive analytic powers, AI can help segment and personalize marketing to improve customer retention and sales. Recommendation engines like those described above come into play as well. In an optimized scenario, a restaurant could synchronize communications with guests across text, email and notifications on its branded app, making timely suggestions based on data on a customer’s preferences, past purchases and other factors.
Generative AI can also help employees draft marketing messages across these platforms to save time and improve sales pitches.
Loyalty Programs
In the NRA’s landscape report, half of adults said they currently participate in a loyalty program at a restaurant or other food service business, and nearly all of those participating saw benefits. No wonder loyalty programs are such an important tool for restaurant marketing. Yet nearly one in four restaurants are dissatisfied with their current loyalty programs, according to the NRN outlook survey.
Industry experts point to AI’s ability to improve loyalty programs as it learns about program members, makes relevant recommendations based on their profiles, and thus motivates them to return and make another purchase. AI can also drive gamification of loyalty programs, with tiers, perks and surprise bonus points to keep customers engaged.
Robotic Chefs
“Flippy,” “Chippy,” “Sippy” and “Drippy” — robots and robotic arms powered by AI to prepare burgers, tortilla chips, beverages and coffee — have gained footholds in some large fast-food chains. Many trials have been launched across the country, and some have been paused to work out the bugs.
Still, experts see robotics as an inevitable part of restaurants’ future. Among their expected advantages are meal-prep consistency, speed, hygiene, ability to work without breaks and lower cost. The current consensus is that restaurant staff and robots would work side by side, with staff members focusing on more creative work, customer relations and problem-solving, while robots handle rote tasks.
Smart Inventory Management
Inventory management software keeps getting smarter, which is timely when so many restaurant managers are looking to operate more efficiently and avoid waste. In fact, the 2024 landscape report showed over half of restaurant managers planning to invest in inventory control and management systems in the coming year, with the hopes of addressing food waste.
When these systems incorporate AI, they can help predict demand, monitor supply and generate purchase orders by analyzing seasonality, customer preferences, menu plans, freshness dates and other factors. In a simple scenario, a purchase order for tomatoes can be issued automatically when tomato inventory dips below a certain threshold.
AI in Scheduling
Given the rising labor costs as described above, restaurant managers are looking to conserve staffing expenses wherever possible — without compromising their customers’ experience. But managers also prioritize staff retention amid a shortage of workers. In the NRN outlook survey, over a third of respondents said they expected to invest in technology for labor management in the coming year, with nearly as many planning to invest in IT to support their employees’ experience, retention and productivity.
AI can improve scheduling by matching employee availability and skill sets to sales forecasts, historical data and other input. If customer demand is predicted to surge or drop off on any given day, scheduling more or fewer kitchen and wait staff can make the difference between good or bad customer service — and between a profitable or unprofitable night. AI scheduling features, such as automated conflict detection, can also flag common, disruptive scheduling errors, including double-booking or scheduling unavailable staff members.
Energy Management
Restaurants consume much more energy per square foot than most other businesses to power freezers, ovens, dishwashers, air conditioners and lighting. But they face the same hotter weather patterns and escalating utility rates as other businesses.
Also like other businesses, restaurants can avail themselves of various AI-enabled tools available on the market, such as energy-monitoring platforms, smart thermostats and predictive maintenance solutions. Some are more tailored to restaurants than others. For instance, one big restaurant supplier is using IoT technology to connect various kitchen appliances to each other and to centralized software for energy management. A specific application uses AI to lower a restaurant’s energy use during periods when peak rates are in effect.
Food Safety
Restaurants prioritize food safety for reasons ranging from reputation to legal repercussions. AI can support this priority in various ways. For example:
One type of AI — computer vision — can interpret whatever a camera can see, a capability that is being used to analyze restaurant inventory quality for safety purposes.
Other AI sensors might monitor refrigeration temperatures for spikes that would spoil food, sending an immediate alert.
Sensors can also identify anomalies, such as unusual vibrations in refrigerators and freezers. Predictive maintenance analytics can use this and other input to forecast equipment failures and head them off.
Intelligent cleaning robots can sanitize surfaces more effectively.
Health Protocols
Beyond safe food handling, restaurants must manage hygiene, pest control, waste management and worker safety — all subject to inspection by local health departments and regulation by federal agencies, such as the Occupational Safety and Health Administration.
AI not only helps address health and safety issues, as described in the section above, but it can also facilitate reporting to inspectors. It does so by automatically keeping managers apprised of all health and safety protocols, tracking adherence, identifying recurring issues in inspection reports and predicting potential compliance lapses before they occur.
Predictive Analytics
Predictive analytics is one of the things AI does best, as it identifies patterns in data and suggests what might come next. The power of predictive analytics is seen in almost all AI applications, ranging from customized marketing to inventory optimization, as restaurants continue to amass more and more data on their customers and operations.
Demand forecasting provides a case in point. AI can make informed predictions about what guests will order, how much and when, based not only on historical sales but also on customer profiles, location, weather, promotions, time of day, holidays and other factors. In turn, this kind of information can help a restaurant orchestrate operations, whether it’s ordering ingredients, scheduling staff or accurately completing other essential tasks to improve its bottom line.
Customer Feedback Analysis
Online reviews can make or break a restaurant’s reputation. On a more positive note, they can also provide useful insights on ways to improve menu offerings, operations and sales.
AI review-monitoring tools can parse customers’ comments across myriad review sites and social media platforms. They can analyze sentiments, respond to some reviews with automated templates, prioritize problematic reviews and make generative AI suggestions to staff on how to craft an appropriate response. These tools can also summarize reviews into regular reports that incorporate performance analytics and trending topics.
Dynamic Pricing
Dynamic pricing is another AI-fueled innovation that is taking hold in restaurants, integrated into POS systems and digital menu boards. Like airlines and ride-sharing services, some big chains are experimenting with raising and lowering menu prices based on demand or time of day.
Some critics have pushed back against early indications of what they call “surge pricing” in the industry. But more restaurants are beginning to experiment with dynamic pricing, countering that they are equally apt to offer bargains during off-peak times. And in some restaurants, people have long been accustomed to pricing variations on lunch versus dinner menus — and during happy hours.
Financials
Restaurants often falter due to lack of attention to essential financial tasks, like accounting and payroll. AI’s sales forecasting prowess and its data capture and classification capabilities provide key benefits for restaurant managers overseeing cash flow, as well. And AI-enhanced accounting software can also flag discrepancies that might indicate errors or fraud.
For example, AI-enhanced bill capture features can reduce the time spent on data entry by scanning invoices into accounting systems. Generative AI is also being integrated into accounting software; it can improve employees’ productivity by helping to draft content, such as purchase orders.
Benefits of AI in the Restaurant Industry
In and of itself, the act of automating tasks, such as taking and filling orders, reduces errors, which is a top priority in restaurant surveys. AI implementations tick this box but can also deliver additional benefits. Among them:
Enhanced customer service: Even as AI delivers customer service benefits, such as customized offerings and error-free ordering, restaurateurs say its biggest contribution may be freeing employees of rote tasks so they can focus more on customer engagement and interaction.
Personalization of customer experience: Customized marketing on a restaurant’s own website or app can yield three times as much digital engagement and increase revenue by up to 10%, according to Boston Consulting Group.
Operational efficiency: When restaurateurs upgrade their technology, they expect to gain the most bang for their investment buck in greater operational efficiency, according to the outlook survey. AI upgrades for automation and data-driven decision-making can help restaurants beat industry benchmarks in areas like inventory turnover and cost of sales.
Cost management: Nearly four in 10 restaurant managers polled by the NRA listed expense reduction as a top objective for the coming year, amid today’s high food, energy and labor costs. AI’s demand forecasting and inventory management can help manage costs in such areas as a restaurant’s supply chain by recommending optimal purchase amounts to prevent overstocking and spoilage, but also to avoid “86’ing” popular menu items in the middle of the dinner rush.
Data-driven decision-making: In the fast-paced restaurant industry, AI enables restaurant managers to make better informed decisions more rapidly, based on predictive business analytics that analyze real-time data and present multiple scenarios for acting on it.
Improvement in food safety: AI-based tools are increasingly used to monitor temperatures, detect contamination, check the accuracy of labeling and track adherence to food safety regulations.
Enhanced marketing and customer loyalty: In addition to the customized marketing capabilities described above, AI’s predictive analytics can also identify customers who are at high risk of churning by analyzing behaviors and suggesting ways to bring that diner back into the fold.
Risk management: AI’s predictive analytics provide a risk management engine for running “what if” scenarios, while also pinpointing potential inconsistencies and even fraud in real-time data.
Limitations of AI in Restaurants
An overriding technology limitation frequently cited by restaurateurs is the difficulty in overcoming data silos and integrating new capabilities into the systems they already have. Nearly four in 10 restaurant managers reported this dissatisfaction in the outlook survey. Other AI limitations include:
High initial costs: At the NRA show, speakers said that many AI capabilities remain out of reach for smaller restaurant owners, though they expect the costs to come down over time. Their advice was to start small — perhaps with marketing applications — rather than rushing to rent a robotic cook.
Loss of human touch: Also at the restaurant show, NRA CEO Michelle Korsmo underscored concerns about robots replacing human creativity and customer engagement, saying: “Now, each of you are at the crossroads where you must figure out: What is that high tech–high touch balance for your business?”
Resistance to change: Whether in digital marketing or other aspects of their operations, restaurants are generally seen as resistant to new technology — or simply too busy focusing on their core business to change. But the challenges that have beset their industry and undermined existing business models are driving change here, as well.
Integrate AI in Your Restaurant Operations With NetSuite
NetSuite is embedding AI capabilities across its cloud-based offerings, including its enterprise resource planning (ERP), accounting and inventory systems. NetSuite has also released NetSuite Connector for MICROS Simphony, enabling restaurants to integrate with Oracle’s POS system and its many API partners for restaurant applications, as well as to import core financial data for reporting and cash reconciliation. Restaurants can replace multiple point solutions with a single suite that provides the foundation for getting the most out of AI.
Restaurants may not be AI pioneers, but they are beginning to embrace the technology to help address challenges ranging from a nationwide labor shortage to an overwhelming surge of data from review sites and social media. Big fast-food chains are leading the way, but small and midsize restaurants are also benefiting as AI’s cost and availability improve.
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AI in Restaurants FAQs
How is AI used in the restaurant/food industry?
Artificial intelligence (AI) is infiltrating the restaurant industry, from front-of-house customer interactions to back-of-house kitchen operations and administration. Examples include AI chatbots that take food orders in drive-throughs, inventory software for reducing waste and virtual assistants that draft marketing copy.
What is an example of AI in the food industry?
Starbucks Deep Brew is an AI system that personalizes marketing campaigns for each customer, evaluating factors like past purchases, time of day and even weather, to deliver targeted messaging. It also analyzes customer preferences to guide the development of new menu items.
How does McDonald’s use AI?
McDonald’s is pursuing a strategy for the global, cloud-based rollout of applications being developed at its Speedee Labs innovation center in Chicago. While major fast-food brands only discuss their AI initiatives selectively, McDonald’s has reported piloting AI chatbots in 100 drive-throughs. In a press release, it also referred more generally to its AI initiatives, such as monitoring equipment performance, reducing business disruptions, diminishing complexity for employees and providing new customer experiences.