QSR TECHNOLOGY


IN THE AGE OF AI AI-driven quality control and inventory management is high on the agenda, according to John Egnor FCSI of JME Design, who has conducted an in-depth research report into AI in the QSR sector. “Its key benefits will be the


ability to monitor food quality and safety in real time, using sensors and cameras to ensure consistent cooking temperatures and detect anomalies, and predictive analytics to optimize inventory by forecasting demand,” he observes. “Robots will handle repetitive tasks like chopping, mixing, and packaging, allowing staff to focus on creative or customer-facing roles.” Douglas K. Fryett of Fryett


Consulting Group also notes that a company in Toronto has developed a piece of automated equipment that in just one square meter can cook 300 or 400 burgers per hour. “It has an optical recognition


system, so it can tell what kind of burger is being cooked, and it has a temperature probe,” he explains. “It also has an AI element that can sense whether a


component is likely to fail soon, so it can send an alert and a technician can be called. Tests have shown that it can save tens of thousands of dollars per year in labor alone.” Automation can optimize


workflows, increase product consistency and accuracy, and reduce labor costs, so it is increasingly the driver of efficiency. Fryett has seen one client explore optical recognition to make pizza production more efficient. “Around 85% of pizzas


sold are pepperoni pizzas, so there is a high level of predictability when someone comes in to order a pizza,” he explains. “With AI-driven optical recognition, when the operator puts a pizza in the oven, the system tracks it until it comes out at the other end, measuring it and comparing it to a model of the ‘ideal’ pizza. Te employee gets instant feedback on how to improve it, and the net result is an increase in customer satisfaction and product quality.” AI is also coming into its own in smart management


“Within the next five years it is realistic to expect some restaurants to adapt their menus in real time according to who is eating what, when and why”


systems that can analyze orders received. Te system can then request ingredients, create inventory, and estimate what a person will order based on their previous orders. “AI is making strides in demand analysis and forecasting and it is at the forefront of innovation,” says Hannify. “However, its true value lies in accelerating data access and analysis – and that requires having the right data infrastructure in place first.” He points to a lack of clarity around what AI can realistically achieve and where its limitations lie,


Equipment will increasingly get smarter to improve efficiency in QSR operations


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but adds that “the potential for AI to dramatically increase the speed and precision of decision- making is significant and continues to grow as adoption and understanding improve. ” Soon, the QSR sector could


be very different, even though the fridges, freezer, fryers and cookers will be doing the same as they do now. What will change is the technology backbone of data collection and analysis. “A fully connected restaurant


where all data flows to a central hub will accelerate decision- making. Within the next five years it is realistic to expect some restaurants to begin adapting their menus in real time, based on who is ordering what, when and why,” says Hannify. “Understanding that faster means you can really double down on marketing.” Whether the QSR segment


can turn that into meaningful change that will improve ROI remains to be seen. After all, it is not only about having the data to drive efficiency, it is about knowing what questions to ask of that data.


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