AI and Restaurants Buzz Research Report
Deloitte’s “How AI is Revolutionizing Restaurants”
The AI and Restaurants Buzz Research Report by Deloitte isn’t just another “AI is coming” puff piece. Instead, it delivers a data-rich, 
If you are a restaurant exec looking to increase your budget with hard-to-track items, this is the report for you. When Panera’s decided to implement self-order, what was the first thing they did? They built out their kitchen infrastructure to handle higher burst cycles. Ovens and coolers. Support assets. People. Physical assets. Then they bought into and implemented self-order. Blaine Hurst. Smart guy.
Not much time or text spent on “Drive Thru”. One initial mention and then gone. 70% of sales? Zero mention of language or multi-lingual. Big in Europe, likely. Those deficiencies point to the document lacking any real-world examples. We include those at the bottom of this article.
AI and Restaurants Buzz Research Report – Key Takeaways and Actionable Data
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AI Adoption Is Real and Growing: 73% of surveyed restaurant execs expect to increase AI investment next year, with only 2% planning to decrease. This isn’t hype—it’s a clear signal that AI is moving from pilot to production1.
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Customer Experience Leads the Charge: Enhancing customer experience is the top goal for AI, cited by 60% of respondents. Think recommendation engines in kiosks and apps, and voice AI in drive-thrus. These aren’t just experiments—63% report daily use of AI for this purpose1.
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Inventory Management Is a Close Second: 55% use AI daily for inventory management, leveraging IoT sensors and predictive analytics to cut waste and optimize supply chains. Another 25% are piloting these solutions1.
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Emerging Use Cases: The “second wave” is AI for customer loyalty and employee experience—both nearing 70% adoption (including pilots). The “third wave” is food prep and new product development, with less than 50% adoption but the highest levels of planned investment. Real-world examples: computer vision for food safety and machine learning for flavor analysis1.
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Regional and Segment Differences: Casual dining and Asian restaurants are leading adopters, especially in inventory management and employee experience. U.S. restaurants lag in some automation areas but lead in conversational voice AI1.
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What’s Actually Being Used: Chatbots are the most widely deployed (60% daily use), followed by machine learning, intelligent automation, and NLP. More advanced tech like conversational voice AI and computer vision is mostly in pilot1.
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Generative AI Is Still Early: Only 9% use generative AI daily, but many are planning to deploy it. Avatars and virtual worlds are even less common, but on the radar1.
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AI Readiness Gaps: Only 20% feel ready on risk and governance, less than 30% on tech infrastructure and talent. Strategy is the only area where most feel somewhat prepared. The more value a company already gets from AI, the more ready they feel for future applications1.
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Biggest Challenges: The top hurdles are identifying scalable use cases, managing risk, and finding technical talent. Notably, lack of executive buy-in or data is not a problem—leadership is on board, and the focus is now on execution1.
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Risk Management Practices: Cybersecurity, ROI tracking, and bias assessment are top priorities for IT leaders. Half the companies don’t include vendor evaluation in their risk process—a potential blind spot1.
AI and Restaurants Buzz Research Report Bottom Line
This isn’t a theoretical report about AI’s potential. Deloitte’s survey of 375 restaurant leaders across 11 countries shows that AI is already delivering value in customer experience and operations. The industry is moving past “why AI?” to “how do we scale and govern it?” The actionable data here is for operators and brands to double down on practical use cases, shore up risk management, and invest in talent and infrastructure to avoid falling behind. If you’re waiting for AI to arrive in restaurants, you’re already late to the party1.
AI in restaurants _ Deloitte Insights-compressed
Real-world examples of AI being deployed in restaurants:
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Burger King & Taco Bell – AI Voice Ordering Drive-Thru: Burger King uses the ACRELEC AI Voice system to streamline drive-thru transactions, speeding up service and improving order accuracy. Taco Bell has rolled out AI voice technology across hundreds of drive-thrus in the U.S., processing millions of orders and reducing wait times. These systems also help staff focus more on hospitality by automating order-taking1.
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Miso Robotics – Flippy: Miso Robotics’ “Flippy” robot is used in restaurant kitchens to automate frying and grilling tasks. Flippy uses AI and computer vision to recognize food items and cook them correctly, reducing labor costs and increasing consistency. CaliExpress by Flippy in Pasadena is a notable example, where the robot handles burger preparation23.
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Creator (San Francisco): This restaurant uses a robot to make custom burgers from scratch, including grinding beef, frying patties, and assembling the finished product—all managed by AI-driven automation2.
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Wilkinson Baking Company – BreadBot: While more bakery-focused, BreadBot is an AI-powered machine that automates bread-making in grocery and restaurant environments, handling everything from mixing to baking2.
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Richtech Robotics – ADAM: ADAM is a robotic system that uses AI to prepare coffee drinks and cocktails, demonstrating how automation can be applied to beverage service in restaurants2.
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Domino’s – AI Call-In Order Assistant: Domino’s is piloting AI-assisted avatars for taking phone orders, using natural language processing to interact with customers and streamline the ordering process4.
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AI in Self-Service Kiosks: Many fast-casual and QSR brands are deploying AI-powered kiosks that provide personalized upselling, dynamic menu adjustments based on inventory and weather, and data-driven insights for restaurant management56. These kiosks analyze customer preferences, predict popular items, and even optimize pricing strategies in real time.
These examples go beyond theoretical applications, showing AI actively improving operations, efficiency, and the customer experience in real restaurant environments1523.
