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AI in Quick Service Restaurants Market Size

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AI in Quick Service Restaurants (QSR) market is projected to grow from $915.3M in 2024 to $12,047.8M by 2034, at a CAGR of 29.4%. North America leads with 32.4% market share and a $266.9M valuation. Key technologies include machine learning and robotics, enhancing order accuracy, efficiency, and personalization. Main drivers are the demand for faster service, labor shortages, and advancements in cloud tech making AI affordable. Challenges include data privacy concerns and integration complexities. Key players include Presto and Omilia, focusing on voice and data-driven solutions.

https://market.us/report/ai-in-quick-service-restaurants-market/

QSR Brands Adopt AI to Cut Refund Losses

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QSR brands are utilizing AI to enhance profitability and reduce losses from false delivery claims, shifting focus from expansion to financial sustainability. AI can automate processes and verify food packing for deliveries, helping to mitigate refund losses. Despite global uncertainties, the food sector remains resilient, presenting expansion opportunities for some brands.

https://qsrmedia.asia/videos/qsr-brands-adopt-ai-cut-refund-losses

Presto Launches Phone Ordering Business Unit, Expanding Its Enterprise-Grade Suite of Voice AI for QSRs

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Presto Phoenix, Inc. launched a phone ordering business unit to enhance its Voice AI offerings for quick-service restaurants (QSRs) at the Restaurant Leadership Conference in Phoenix. CEO Gee Lefevre emphasized the excitement of introducing simpler phone ordering, responding to customer demand for comprehensive Voice AI solutions. The company aims to be the preferred AI partner for restaurant automation, focusing on drive-thru and now phone ordering technology. Presto seeks to deliver a full suite of AI solutions to drive revenue, reduce labor costs, and improve customer experiences.

https://www.morningstar.com/news/business-wire/20250414646430/presto-launches-phone-ordering-business-unit-expanding-its-enterprise-grade-suite-of-voice-ai-for-qsrs

Quick-Service Restaurants Embrace Digital Transformation, AI Revolution

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QSRs like Taco Bell are investing in AI to enhance speed and accuracy, reduce labor costs, and transform customer engagement. Digital transformation via mobile ordering, AI-driven drive-thrus, and predictive inventory is reshaping operations. Innovations include mobile apps for ordering, AI voice assistants for drive-thru interactions, and predictive analytics for demand forecasting. While technology aids efficiency and personalization, challenges such as high costs and workforce resistance persist. In a competitive landscape, successful QSRs blend technology with human touch, focusing on strategic real estate that supports digital capabilities.

https://rebusinessonline.com/quick-service-restaurants-embrace-digital-transformation-ai-revolution/

How Predictive AI Helps QSRs Keep Customers Coming Back

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Predictive AI enhances customer engagement for QSRs by personalizing offers and anticipating needs based on behavioral data, improving loyalty program effectiveness and retention. Unlike generic offers, it delivers timely, specific promotions that encourage repeat orders, reducing churn. To maximize this technology, QSRs need coherent data systems like a customer data cloud to unify customer profiles, allowing precise targeting and real-time adjustments. Ultimately, predictive AI empowers businesses to proactively engage diners, fostering long-term loyalty and growth.

https://www.qsrmagazine.com/story/how-predictive-ai-helps-qsrs-keep-customers-coming-back/

How to Embrace Tech and AI, From a Restaurant Executive

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Restaurant executive emphasizes embracing technology and AI to meet changing customer expectations and improve operations. Reliance on the internet and mobile apps surged post-COVID, offering convenience and personalization. AI enhances customer experiences via personalized recommendations and chatbots, boosting efficiency and data insights. Embracing technology is essential for future growth and maintaining competitive advantage in the restaurant industry.

https://www.qsrmagazine.com/story/how-to-embrace-tech-and-ai-from-a-restaurant-executive/

Hi Auto Gains $15m to Automate Drive-through Orders With AI

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Hi Auto raised $15M to enhance AI-driven drive-through order systems, achieving over 96% order accuracy amid rising labor costs. The funding will support scaling operations and improving product offerings, addressing challenges like labor turnover. Their technology features noise-cancellation and utilizes real-time data for upselling, aiding QSRs like Burger King and Popeyes in maintaining profitability.

https://finance.yahoo.com/news/hi-auto-gains-15m-automate-094900688.html

Papa Johns Looks to Reclaim Tech Leadership Through AI Innovation

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Papa Johns is enhancing its technology leadership by partnering with Google Cloud, launching an innovation team called PJX. They aim to improve customer experiences through AI-driven suggestive ordering, personalized marketing, and voice ordering. The cloud-based system will assist in order predictions and promotions. With declining sales, Papa Johns seeks to reclaim its tech edge and create a personalized pizza experience, reflecting their historical role as a pizza tech pioneer.

https://www.qsrmagazine.com/story/with-sales-down-papa-johns-looks-to-reclaim-tech-leadership-through-ai-innovation/

Why Yum! Brands’ AI Move Is Worth Watching

Yum! Brands plans to implement AI automation in 500 restaurants, aiming to enhance efficiency in drive-thru ordering and operations. Collaborating with NVIDIA, this initiative sets a significant precedent for the fast food industry, influencing how automation is approached by competitors. The strategy will improve marketing with personalized offers while raising concerns about over-automation and loss of personal service. This move could redefine customer expectations in quick-service restaurants, balancing technology with the human touch.

https://www.thedrum.com/news/2025/03/21/why-yum-brands-ai-move-worth-watching-and-what-it-says-about-the-future-fast-food-3

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