The smarter tech creating smarter restaurants

Restaurant technology has entered a new phase, defined less by individual tools and more by intelligent systems that connect operations end to end. AI is now embedded across payments, reservations, workforce management, customer-facing platforms and back-of-house operations, shifting technology from a support function to something that can help operators make decisions.

Glenn Tait, product director at Zonal, believes that AI delivers the greatest efficiency gains when it accelerates processes and provides data-driven recommendations. “We take a ‘human in the middle’ stance, where AI outputs are presented as options or recommendations, backed by data, rather than final decisions,” he says.

“Users of AI need to understand why an AI model has made a particular decision, which is why transparency is key to building trust. By combining AI’s speed and analytical power with human expertise and oversight, businesses can achieve efficiency without sacrificing accountability or strategic insight.”

Rather than simply capturing data or automating tasks, today’s platforms are able to analyse information in real time, predict outcomes and prompt action. The timing couldn’t be any better: as costs rise and margins tighten, operators are looking to technology not just to digitise processes, but to improve performance, consistency and guest experience.

Nowhere is this shift clearer than in core operational systems such as POS, payments and reservations, where AI is reshaping how restaurants interact with guests. Payments platforms are evolving into customer intelligence hubs, automatically building profiles that support loyalty, marketing and personalisation, while also strengthening security through advanced fraud detection and authentication.

In reservations, AI-powered tools are handling enquiries, managing bookings and surfacing information around the clock, reducing friction for diners and freeing up staff time. Across these systems, the emphasis is on integration and ease of use: technology that works quietly in the background, removing manual steps while also capturing insights.

A similar pattern is emerging in workforce and labour management, an area under intense pressure from rising costs and ongoing recruitment challenges. AI-driven scheduling, forecasting and communication tools are helping operators align staffing more closely with demand, while also giving managers clearer, real-time visibility of performance indicators beyond simple labour hours. Rather than replacing people, these systems are designed to remove administrative burden and support faster decision-making on the floor and in the kitchen. The result is a more agile operating model, where managers can respond to changing conditions without being locked into rigid processes or spending hours compiling reports.

Behind the scenes, AI is also transforming back-of-house operations and data analysis, where its impact is often less visible but potentially more significant. Predictive forecasting, automated ordering and real-time decision support are allowing kitchens to better match production to demand, reducing waste and stabilising costs. At the same time, the growing ability to combine front- and back-of-house data is giving operators a more complete picture of performance. The common thread across all these developments is not technology for its own sake, but systems designed to surface the right information at the right moment, enabling smarter action across the business.

“Hospitality operators have long utilised technology for visibility - seeing what’s happening right now so they can make informed decisions about what to do next,” says a spokesperson for The Access Group.

“Procure Wizard Evo, our re-imaged purchase to pay solution and other similar AI-powered hospitality technologies are fundamentally changing this by providing foresight - predicting what will happen so operators can be proactive rather than reactive. For example, as AI can quickly analyse weather patterns, historical business data, and market trends, a smart system has the ability to say ‘It’s sunny today – prediction of £4,000 in sales’. This allows operators to make precise operational adjustments before the day even begins.”

Reservations

AI is starting to have a big effect on reservations, with many larger operators exploring tools that can take reservations autonomously and respond to guest enquiries. OpenTable recently partnered with voice recognition specialist Poly AI to help restaurants maximise revenue and free up time spent fielding questions.

“AI voice solutions help restaurants answer every diner call 24/7, saving them time and resources without losing a personal tone,” says Sasha Shaker, senior director at OpenTable UK and Ireland.

OpenTable is also using AI to make booking more frictionless for guests.

“Today’s diners are very savvy and often want to know exactly what they’re getting into before they show up,” Shaker continues. “Our AI Concierge tool, available on more than 60,000 OpenTable restaurant profiles globally, centralises information from each restaurant, including menus, reviews, and restaurant descriptions, making it faster and more intuitive for diners to get the information they need. Diners can chat as if they are messaging a friend and ask questions that help them make smarter reservation choices in seconds.”

At TripleSeat, an event management and booking system for hospitality businesses that helps streamline event enquiries, proposals, contracts, and payments, the use of AI and automation is focused on improving productivity, responsiveness, and decision-making for hospitality sales and operations teams.

“We use automation to streamline lead management, follow-ups, and reporting, while AI-powered tools help users move faster without losing personalisation,” says UK marketing director John Karemy.

Later this year, TripleSeat will release a new version of AI Compose that provides more context-aware drafting for emails and communications. It will help users quickly create polished responses, proposals, and follow-ups that reflect brand voice, event details, and customer history, significantly reducing the time spent writing while maintaining a personal touch.

TripleSeat is also set to launch an AI Sales Assistant, designed to support sales teams throughout the lifecycle of an event by surfacing insights, highlighting priority leads, and prompting next best actions.

Workforce management

App-based staff scheduling and communication tools are a relatively new development in the hospitality space, but more and more larger groups are starting to invest in them. The difference now is that many of these platforms are explicitly powered by AI.

Paul Watson, vice president of hospitality at next-generation workforce management platform Sona, says that AI and smart systems are changing the rhythm of the day. Instead of managers spending hours stitching together rotas, reports, HR updates and ‘what’s going on?’ conversations, technology is bringing everything into a single operational picture, helping managers – and those who report to them – focus on what really matters at any given moment.

“At their best, smart systems help managers make better decisions in real time, rather than just producing data for them to work through,” he says. “This includes staffing levels and labour rules, but increasingly also indicators that influence performance, such as onboarding progress, training gaps, attrition risk and engagement. The result is less time spent hunting for and collating information, and more focused time acting on it.”

Sona is working with Loungers – the company behind the Lounge, Cosy Club and Brightside brands – as it continues to scale up to more than 300 sites.

“Like many fast-growing operators, their focus isn’t simply on adding new technology, but on using it in a way that genuinely supports people on the ground,” Watson continues. “That means giving GMs and site teams the autonomy and trust they need to run great services, while using AI to remove friction, save time and make day-to-day decision-making easier.”

Sona says operators want to stay agile as complexity increases and allocate labour more effectively without losing sight of hospitality fundamentals. That means adopting technology that evolves alongside the business, rather than locking teams into rigid processes.

EPOS company Tabology has also recently introduced AI into its staff scheduling module. It can now generate accurate sales forecasts at the click of a button by combining data from previous sales with upcoming bookings.

“These are pulled through to the rota, which then calculates projected wage-to-sales percentages as you build it,” says Phil Neale, managing director of hospitality at Tabology. “This makes it easier for operators to keep on top of labour costs, while also cutting admin workload for managers so they can focus more on customer service.”

Customer facing systems

What was regarded as tech for only the very biggest operators just a few years back has moved into the mainstream with many QSR restaurant brands now turning to self-service kiosks and mobile ordering. Where McDonald’s blazed a trail others have followed, with the likes of Slim Chicken’s, Burger King, Dave’s Hot Chicken, Wingstop and many others all taking advantage of the benefits of using ordering kiosks - higher average spend, increased order personalisation, quicker serve times and lower staffing costs - as well as smaller brands such as HOP Vietnamese and Honest Burgers’ Smash + Grab.

Where operators were once sceptical that people might prefer speaking to a person to ordering via a machine, now they are starting to embrace the further possibilities that such technology can offer. With ConnectSmart Host from QSR Automations by Crunchtime, for example, customers can use the technology to make a reservation, add themselves to a wait list and stay updated on their booking and ordering status through two-way SMS texting. They can automatically remove themselves from the queue should they decide to, all without having to speak to a person.

The continued progress being made in AI is only going to create more opportunities for operators. Looking to the future, AI might be able to use face or number plate recognition to automatically provide regular customers with a more personalised service, using a customer’s previous purchase data to make menu suggestions or offer tailored rewards or discounts at the point of purchase. AI technology can also be used to provide customers with personalised menus based on either their preferences or dietary needs, automatically directing them to only dishes on the menu that they can eat.

Fast-food fried chicken restaurant Popeyes is already using AI at its drive-thrus to improve the customer experience. Screens take a customer’s order in a conversational way while a digital display provides guests with visual confirmation that their order has been understood properly. Technology can answer questions about what ingredients are included in a given item, as well as answer simple queries, and during trials it learned to recommend meal combinations based on a customer’s preference.

“AI, automation and smart systems are reshaping day-to-day operations in the hospitality sector by streamlining processes, improving efficiency and enhancing customer experiences,” says Glenn Tait, product director at Zonal. “Importantly, this shift demonstrates redeployment, rather than replacement of staff, allowing employees to step away from repetitive administrative tasks to those that require, or are enhanced by, human interaction.

“AI tools in hospitality should be geared around allowing teams to do their jobs more efficiently by speeding up the decision-making process and reducing time spent on manual operations, rather than replacing valuable members of the team.”

Payments and POS

Over the past decade, restaurant payments and POS systems have evolved from bulky, static terminals into flexible, cloud-connected platforms that are now integral to hospitality operations. This transformation has been driven by changing consumer behaviour, new payment standards, and rising expectations for speed, convenience, and integration from both restaurants and customers. So, what’s next?

Loyalty schemes are set to become increasingly important as competition for customers intensifies. In recent years, many larger restaurant groups, including Pizza Express, Nando’s, and Wagamama, have launched sophisticated programs. Those yet to implement such schemes are likely to follow. While developing a custom app can be a costly undertaking, independent operators can still leverage loyalty features that are increasingly built into modern POS and payments systems.

For example, Square offers a suite of marketing and customer engagement features that integrate directly with its POS and payments system. This makes it easier for restaurants to attract and retain repeat customers without relying on separate tools.

Every time a customer makes a payment, Square can automatically generate a profile containing contact details such as phone numbers and email addresses. These profiles are stored in the Square Customer Directory, which functions as a basic CRM, allowing operators to track visit history, purchase behavior, and preferences. Operators can also use these profiles to market directly to customers and create loyalty schemes, where repeat visitors earn points or rewards based on visits or spending.

As payment technologies advance, so do fraud risks. The industry is increasingly adopting stronger encryption, real-time fraud monitoring, and compliance measures to protect both operators and guests. Biometric authentication (such as fingerprint or facial recognition) and tokenization — which replaces sensitive card data with unique digital tokens — are expected to grow in use as security becomes even more central to customer trust. Operators should also watch developments in open banking technology, which could help reduce card transaction fees.

Back of house tech

While there is a tendency to think about new and emerging technology in restaurants only in terms of that which can be seen by the customer, it is with back of house operations where the real magic happens. Technology that can help with food prep, increase speed of delivery and reduce wait times, as well as automate time-consuming tasks is already helping operators to put more focus on looking after the customer.

The use of AI assistants such as CoPilot will become key back of house, according to business management software company The Access Group, where people can ask questions in plain language and get clear answers in the format, detail, and language they need, as well as Feed, which provides a personalised, live stream of tasks, alerts, and updates, so people always know what needs their attention the most without hunting for it.

Access says that critical information such as a change of allergens in a dish or GP across different locations can be accessible ‘during the chaos of kitchen operations’, allowing informed decisions to be made in the moment. “As a head chef, I had eight chefs waiting outside of the front door of the restaurant. I would put the key in the door, turn the alarm off with my fob, rip off my jacket, and I did not stop until service was over,” says Andy Sestak, a commercial specialist for Access’ hospitality purchasing software Procure Wizard Evo and who previously worked as a head chef at Wagamama.

“You’re setting the sections up, making sure the gas and temperature checks are all done. Ordering. Cooking. There’s no spare time. But with Copilot and Feed you can shout into your phone ‘What’s my current take? What’s my taking yesterday?’ CoPilot can tell me I made £6,800. Straight away I know I had forecast £7,000. I’ve probably overspent about £400 on labour. So, I can then tell one of the chefs – ‘John, get that section set up, mate. At 1 o’clock you can go’.”

Shamik Morjaria, insights and technology specialist at Crunchtime, also sees the value in using AI to improve back of house functions. “Good AI will help GMs automate repeatable workflows and support faster, better decision-making, allowing GMs to spend more time on the floor with employees and customers,” he says.

“We view these technologies as a way to eliminate guesswork. Instead of managers spending hours manually calculating food orders or building schedules on spreadsheets, smart systems automate these ‘controllable expenses’.”

For example, predictive analytics and AI forecasting allow businesses to anticipate demand with high accuracy, ensuring that inventory and staffing levels are perfectly aligned with actual guest traffic, says Morjaria, which reduces waste and stabilises labour costs.

According to Morjaria, the most effective applications are ones that directly influence food and labour costs. “AI-driven forecasting, automated scheduling, kitchen optimisation, and real-time decision support are examples where operators are seeing concrete value because these tools are rooted in operational reality.”

Again, looking to the future, technology will further improve collaboration between front and back-of-house as it develops, according to Nick Freeston, director of client management EMEA at QSR Automations by Crunchtime.

“We’re extremely excited about the next wave of connected, real-time restaurant systems. For example, with our client, Dave’s Hot Chicken, we’re working with them to test ‘dynamic quote times’, which will allow them to match the order ready time, exactly to when the customer arrives.”

Freeston says that QSR Automations by Crunchtime partners with a range of fast-growing restaurant brands worldwide that need to be able to plan for the future. Other examples of brands it works with include ramen concept Bone Daddies, which has leveraged its technology and data to streamline efficiencies across back-of-house.

Bone Daddies wanted to be able to deliver its ramen to customers within 10 minutes and by using QSR Automations by Crunchtime’s technology, on average it was able to create a four-minute ramen and overall timings improved in the kitchen by as much as 10 minutes. “The data enables them to set benchmarks, manage the bottom line, together with focusing the team to be more efficient,” says Freeston.

Cook time variances have also enabled Bone Daddies to see any problems with the cooking of a dish, while table turns, originally at 52 minutes, dropped to 43 minutes.

Data insights and business intelligence

One area where restaurant technology has made huge advancements over the past few years is the amount of data that can be captured and the quality of information it can provide operators.

Morjaria, says Crunchtime’s merger with QSR Automations has unlocked a ‘huge opportunity’ through potential product integrations and the data that can be provided.

“Data becomes exponentially more powerful, when back-of-house and front-of-house insights are communicating harmoniously together,” he says. “By bringing together speed-of-service metrics, staffing data, inventory usage, audit results and sales, it creates a full picture for an operator of what’s working, what needs attention and what to prioritise next.”

When it comes to the crucial role of forecasting, developments in AI are helping managers with their decision making. QSR Automations by Crunchtime’s most effective uses of AI include forecasting, with proprietary machine learning algorithms that analyse historical data, weather and events to predict future sales within a narrow margin of error; and providing managers with clear, timely guidance on how to refine the forecast and apply it to daily operations.

“Our algorithms continuously monitor forecast data and surface the right next steps directly in managers’ daily workflows,” says Morjaria. “With these AI-powered recommendations, managers no longer have to worry about missing critical steps like reviewing forecasts, comparing performance, or accounting for factors like weather.”

After generating an accurate forecast, the system tells kitchen managers exactly how much food to prep throughout the day, and how much food to order from each supplier, making it easy to reduce waste and prepare the right amount of food to meet demand. In addition to automated task alerts and follow-up actions, it automates food safety checks and task lists across thousands of locations to ensure brand consistency.

“The most exciting development for me is predictive PAR (periodic automatic replenishment) and smart ordering - systems that learn to predict your net sales for the next few days, because net sales directly control your cost of sales,” says Andy Sestak, a commercial specialist for Access’ hospitality purchasing software Procure Wizard Evo.

“I’ve spent years working with spreadsheets where you input the sales forecast, and it tells you how many yaki sobas to make, how many katsu curries to prep. Then I click refresh, print out prep sheets, and spend 20-30 minutes before every shift manually distributing them to chefs to prevent over-prepping. This has been the reality for years, so imagine all that time you’re going to save.

“[With] predictive ordering, prep planning, and PAR management we’re going to have to completely rewrite our ROI calculator because the implications are going to rip up the rulebook on ROI.”

Sestak says he could go into any restaurant, look at a GP and make it better just by putting some fundamental steps in place. “If someone said to me, here’s some tools to give you what your forecasting will be, I’m going to use that information.

“If the system has told me I’m going to make £7,000 today, therefore I need twenty-nine burgers, then I’m going to prep salad for twenty-nine things. I’m going to leave the rest of the tomatoes in the fridge and not cut them.”

Zonal is also working with its customers to provide better forecasting at a product level. It is augmenting its existing suggested ordering solution to help venues plan more accurately, reduce waste and speed up the ordering process.

“Labour costs are still high, and while we’re not a workforce management platform, we’re using data to support smarter staffing decisions,” says Glenn Tait, product director at Zonal.

In addition to this, Zonal is also looking at ways it can use its customers’ own data and compare against external data sources, such as competitor’s websites, Tripadvisor and Google, providing operators with competitive insights with weighted recommendations on what matters.

“By surfacing the most relevant data and filtering out noise, we empower businesses to make faster, more informed decisions and stay ahead in a highly competitive market,” adds Tait.