From Bots to Bowls: The AI Evolution Reshaping Fast Dining Experiences

Cybertrucks, music generated from brain waves, and shoppable TV. 2023 has unquestionably ushered in its fair share of technological advancements, with none more omnipresent than everyone’s new favorite phrase: AI.

As artificial intelligence carries on its campaign for global domination, we want to take a moment to think about what impacts AI and personalization will have on quick service restaurants, casual-dining restaurants, and consumer habits as we step foot into 2024.

In the past few years, QSRs have invested heavily in optimizing customer experiences, through mobile apps, self-serve kiosks, and personalized offers. So it comes as no surprise that with AI’s  pervasive “nature,” it too has begun rearing its head in the QSR space. And sometimes, an extremely uncomfortable one at that. (The next generation of conversational kiosks).

A high demand for drive-thru orders, curbside pick-ups, and home deliveries indicates a permanent shift in consumer dining habits. Brands struggle to keep up with evolving consumer preferences, which is why AI has become the Ace up every brand’s sleeve to adapt to an increasingly demanding and increasingly digital consumer landscape.

What has caused the demand for AI in the QSR space?

The surge in demand for AI solutions stems from a direct response to confronting challenges like the pervasive issue of labor and supply chain shortages. Roughly half of QSR operators acknowledge the recruitment and retention of employees as a paramount challenge, with the replacement of a single hourly employee incurring costs ranging from $3,500 to $10,000. This challenge has a ripple effect, extending the financial strain to the industry’s bottom line; turnover costs the average restaurant $150,000 annually. Further, 55% of establishments report heightened costs and prolonged customer wait times and 36% observe an increase in running costs, exacerbating the financial strain.

Amid these challenges, the intricate dance of managing inventory has become an ongoing obstacle. Fluctuating demand, the expectation for variety, and the imperative to minimize waste collectively contribute to inventory management’s complexity. Within this challenging scenario, AI emerges as a beacon of hope for QSRs, offering a transformative solution to streamline operations, enhance efficiency, and meet the evolving consumer expectations.

What are AI’s advantages and disadvantages for QSRs and Casual-Dining?

Addressing Labor Shortage

AI-powered ordering alleviates the impact of understaffed restaurants and introduces automated avatars and kiosks for seamless order processing. These innovations not only increase operational efficiency, but also contribute to a consistent customer experience. A recent NVIDIA study showed that automated avatars:

  • Increased order size by 15–18%
  • Extended operations by 12–16 hours
  • Reduced customer wait time
  • Provided upsell recommendations

Kitchen Automation

In the quest for efficiency and quality, brands embrace AI-driven solutions for kitchen automation. Platforms like Kwali for pizza shops employ AI to inspect food quality, reduce waste, ensure accurate order fulfillment, and enhance overall kitchen productivity.

Analytics for Efficiency

Platforms like RadiusAi are pivotal in optimizing restaurant layouts by providing heat maps to unlock valuable insights like understanding traffic flows, optimizing layouts for convenience, and identifying potential hazards.

Forecasting and Inventory Management

Solutions like NVIDIA RAPIDS enable accurate demand forecasting and inventory monitoring, ensuring that brands have the correct food item quantity at the right locations and times. This safeguards against supply chain disruptions and contributes to improved customer satisfaction.

Optimizing Delivery Speeds

By optimizing delivery routes and improving service, Upper enhances the overall customer experience, providing more accurate delivery windows, ensuring food freshness, and reducing environmental impact.

Personalization and Customer Experience

From streamlining the ordering process to customizing orders, AI ensures speed and accuracy. Improved customer experiences foster loyalty and translate into increased revenue for brands. For example, there’s Tori, which takes 100% of orders and integrates with POS, KDS, headsets, and speaker posts.

Waste Reduction

Through advanced forecasting and inventory management, Winnow Solutions helps brands minimize waste, ensuring that restaurants stock the right products and closely monitor food quality, safety, and waste. 

In embracing AI technologies, brands are not just addressing immediate challenges but also future-proofing operations. So, how are brands putting these AI implementations to work?

Real-life examples: Artificial Intelligence at Work


Chipotle has been a tech trend-setter for years and even has their own venture capital fund for new tech investment. That has included quite a bit of AI. Last year, Chiptole began testing a system from PreciTaste that monitors inventory levels and tells restaurants when to restock makelines.

The technology uses sensors to monitor food pans in real-time while also tracking inventory levels and analyzing traffic patterns to help forecast demand. It can even take into account weather and local events that could impact traffic.

Chipotle is also testing the AI-powered robot, Chippy, to make their tortilla chips, and their website features an AI chatbot called Pepper that can field customer questions and complaints.


Wendy’s partnered with Google Cloud to test a new voice-activated AI system for their drive-thru lanes. Launching in Columbus, Ohio, this pilot program aims to streamline the ordering process, improve accuracy, and ultimately create a more positive customer experience.

Powered by Google’s generative AI and large language models (LLMs), the system will allow customers to place their orders using voice commands instead of interacting with human employees. This could lead to faster order times, reduced errors, and increased customer and staff efficiency.

Del Taco

In a move to further automate their drive-thru lanes, Del Taco expanded their  partnership with Presto Automation. This follows a successful initial test of Presto Voice, a voice AI system, which resulted in over 95% of the restaurant processing orders without human intervention. The system can accurately recognize and interpret customer orders, even in noisy drive-thru environments. And using LLMs, the system understands the human language’s nuances, allowing for more conversational interactions and the handling of complex requests. Once the order is understood, the system seamlessly transmits to the POS and kitchen display systems, ensuring efficient order fulfillment.


Domino’s will utilize Microsoft’s Azure OpenAI Service to create a generative AI assistant capable of handling store tasks, including inventory management, ingredient ordering, and staff scheduling. Generative AI personalizes the ordering process and provides customers with relevant suggestions and recommendations. Additionally, it will generate automated purchase orders for suppliers based on projected needs, monitor stock levels, notify managers of potential shortages, optimize storage space, and ensure efficient inventory utilization.

As the industry pivots towards increasingly personalized experiences, a pertinent question arises: How much personalization is too much? Consumers appreciate AI’s conveniences, but where do we draw the line between optimization and invasion?

Smile for the… menu?

Say goodbye to fumbling for your wallet at the pay window. ALPR (Automatic License Plate Recognition) automatically identifies your car and charges your pre-registered account, streamlining the drive-thru process. In addition, customers see personalized menu boards tailored to show their preferences and automatically trigger order preparation as soon as their car enters the drive-thru. It may seem like this is another way to save time and improve the ordering experience, but do you want the cars behind you to see your favorite items or how frequently you order?

And to take a step further into creepy, get ready for a dystopian future where restaurants know exactly what you want before opening your mouth. Wahlburgers, the burger chain owned by the Wahlberg brothers, uses AI-powered cameras to analyze customers’ faces and predict their orders. Self-serve kiosk cameras  scan your face and categorize you by gender, age, mood, and even distraction level. Based on this data, the kiosk displays menu items more likely to appeal to you. For example, a woman might see grilled chicken salads on her menu, while a man might see burgers. Customers are not explicitly told the technology scans their faces and collects their data. Yikes! This tech reinforces gender stereotypes and assumptions about what people will like based solely on their appearance. Customers may also find the idea of a machine scanning their faces, categorizing them, and accessing their order history unsettling. Questions arise about data security, the storage of facial biometrics, and the potential misuse or unauthorized access to this sensitive information.

As we tread further into this AI-driven era, the conclusion becomes clear. There is a delicate dance between the allure of enhanced convenience and the need to safeguard privacy and individual autonomy. Striking the right balance in deploying these technologies is crucial to ensuring that the benefits of AI in food ordering are realized without encroaching upon the boundaries of personal space and consumer choice. As the tech landscape continues to evolve, it is essential to foster a dialogue around the ethical considerations of AI applications, seeking a harmonious coexistence between innovation and consumer well-being.

Will you have ‘the usual’?

Consumers exhibit complexity in their behaviors. As the renowned British advertising figure David Ogilvy emphasized, “Consumers don’t think how they feel. They don’t say what they think, and they don’t do what they say.” Despite their expressed expectations regarding personalization, consumers are unequivocal about their privacy concerns, creating a paradox for marketers. The “State of Connected Customers” research by Salesforce reveals that 72% of customers would cease purchasing a company’s products and services due to privacy apprehensions. This underscores the necessity for companies to approach the utilization of collected data strategically, navigating the delicate balance between personalization and privacy in response to this paradox.

We may not have flying cars yet, but we get closer to living like the Jetsons each day. In the evolving landscape of technological integration, the journey into the realm of AI in QSRs and casual-dining establishments is thrilling and complex. AI advancements are not just reshaping how we order and receive food; they are challenging us to reevaluate the delicate balance between technological convenience and preserving personal boundaries.