Fast-food chains leverage AI to reduce waste and boost profits

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The fast-food industry has long focused on speed, consistency, and cost control. In recent years, the sector has begun using one of its most valuable assets: vast amounts of customer data. As quick-service restaurants gather detailed information about purchasing behaviors, a new technological tool has emerged to turn that data into action. From forecasting demand to streamlining supply chains, AI is becoming essential for major brands such as McDonald’s, Taco Bell and newer players like Juici Patties.

AI’s role in inventory management

One of AI’s most promising uses in the fast-food sector is predictive analytics for inventory. Stockouts and over-ordering have long challenged restaurants, cutting into revenue and sustainability goals. Juici Patties, which runs more than 70 locations in Florida, New York and Jamaica, faced these problems when it entered the US market. To fix supply gaps, the company added AI tools that predict demand and spot supply problems before they disrupt stores.

Stuart Levy, the company’s chief technology officer, said AI helps Juici Patties keep its distribution centers stocked with branded packaging and ingredients. By analyzing real-time point-of-sale data along with factors such as weather and local events, the AI generates forecasts that guide purchasing. The result is fewer stockouts and smoother expansion into new markets.

Enhancing operational efficiency

AI’s reach goes well beyond inventory. Domino’s Pizza and Microsoft worked together on a generative-AI assistant that saves managers time on tasks like ingredient ordering and inventory checks. Starbucks also partnered with Microsoft to use generative AI in product development. Yum Brands, which owns Taco Bell and KFC, teamed up with Nvidia to improve internal analytics and labor management.

The need for efficiency is clear. Spencer Michiel, a restaurant technology advisor at Back of House, said brands built on speed and consistency want tools that remove manual work and cut costs. For many, AI builds on existing operating procedures by adding advanced forecasting and real-time tweaks.

Reducing food waste and costs

Poor forecasting and inefficient purchasing drive food waste in restaurants. Over-ordering means food expires before use, forcing operators to throw it away or raise prices to recover costs. With AI, restaurants can make better buying decisions with location-specific forecasts that factor in local traffic or events.

Industry consultant Stephen Zagor called food waste one of the sector’s biggest costs. Small gains in purchasing accuracy can protect tight profit margins. In an industry where five cents on a burger can mean millions in added revenue, smart ordering makes a difference.

AI can also flag ingredient swaps that boost profits without changing quality. Its ability to balance cost and customer experience gives fast-food operators a strong reason to keep investing in the technology. Concerns about workforce cuts also linger, though experts say AI’s main role is to support operations, not replace staff.

Despite these challenges, AI’s growth in fast food shows no signs of slowing. Juici Patties, for example, used AI to find that customers wanted food earlier in the day. By opening earlier, the chain gained steady daily sales increases. As more chains adopt similar tools, AI will keep improving supply chains, cutting waste and protecting tight margins.

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