Technology

Uncovering lessons from early use of AI in fast food

Bob Vergidis, founder and chief vision officer of pointofsale.cloud, discusses how the restaurant industry is learning that rushing into AI without a clear plan can hurt trust, but a thoughtful, intentional approach can unlock incredible possibilities.

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November 19, 2024 by Bob Vergidis — Chief Vision Officer, pointofsale.cloud

When we make a purchase, two factors often stand out: convenience and simplicity. Whether we consciously think about it or not, these elements play a huge role in what we choose to buy and where we go. Restaurants are catching on and increasingly turning to artificial intelligence to deliver smoother, more streamlined experiences. While some early successes show the promise of this technology, there are also lessons reminding us that just because AI can be used doesn't always mean it's ready for the task.

May AI take your order?

Voice AI has been one of the most exciting areas for fast-food AI adoption. White Castle was one of the early adopters, piloting voice programs to handle drive-thru orders. Now, Taco Bell is aiming to introduce AI to hundreds of drive-throughs by the end of 2024.

McDonald's also jumped into the fray with a bold experiment, rolling out AI at over 100 locations to take customer orders at the drive-through. The idea made sense—handling the steady stream of cars with AI would free up employees to focus on preparing food, improving in-store service, and keeping operations smooth.

However, reality didn't quite match the vision. While AI sounded great on paper, the technology struggles with real-world challenges. Background noise from cars and varying accents made it difficult for the AI to understand orders accurately. Common phrases like "hold the pickles"led to mix-ups, frustrating customers. Some felt the system wasn't ready for prime time, and McDonald's eventually hit pause on the project.

Still, this feels less like a failure and more like a reset. The experiment highlighted areas for improvement, and advancements in AI continue to evolve. The hope is that future versions of the technology will achieve over 90% accuracy, allowing AI to handle orders with minimal mistakes. When that happens, we may see robots running drive-thrus in a way that meets customer expectations.

Dynamic Pricing: A different take on AI

Wendy's took a unique approach to AI earlier this year by introducing "dynamic pricing." The goal was to adjust menu prices based on demand, similar to a happy hour. During slower times, prices would drop to attract more customers. It's a familiar concept t— airlines and gas stations have been doing this for years — but it was new to fast food.

Unfortunately, the rollout didn't go as planned. Customers misunderstood the concept, confusing it with surge pricing, where prices increase during busy periods. This led to concerns about unpredictability, and fears spread online that prices might rise unexpectedly. Even though Wendy's goal was to offer savings, the messaging missed the mark. The backlash turned what could have been a creative innovation into a PR challenge.

This experience highlights how important it is to clearly communicate changes to customers. If people don't understand how something benefits them, even the best ideas can fall flat.

What can we learn?

The examples of McDonald's and Wendy's show both the promise and the pitfalls of AI in the restaurant industry. AI has enormous potential to make dining faster, easier, and more personalized, but its success depends on thoughtful implementation and clear communication.
First, it's important to recognize that innovation often involves trial and error. Early experiments, even those that stumble, lay the groundwork for future improvements. Restaurants that are willing to take risks and learn from their experiences should be applauded for pushing the industry forward.

Second, customers need to feel the value of new technology. Whether it's faster service, personalized experiences, or savings, the benefits should be obvious and easy to understand. Transparent communication is key to managing expectations and helping customers embrace change.

Is it all about the customer?

Absolutely. At its core, the restaurant business is about great food, excellent service, and providing value. Any new technology should amplify these core principles, not complicate them. For example, if AI is customer-facing, it needs to create a seamless, enjoyable experience. If it's behind the scenes, it should improve speed, quality, or efficiency in a way customers can notice.

AI used as a gimmick might generate initial buzz, but lasting success depends on delivering real value. Customers need to see how the technology improves their experience — and they need to trust it.

Looking Ahead

The road to integrating AI into restaurants is still unfolding. While some early experiments have hit bumps, they provide valuable insights that will shape future efforts. The industry is learning that rushing into AI without a clear plan can hurt trust, but a thoughtful, intentional approach can unlock incredible possibilities.
With patience, careful communication, and a focus on enhancing the customer experience, AI has the potential to transform dining. It's not about racing to be first; it's about getting it right. When done well, AI can bring more convenience and simplicity to dining out, benefiting both customers and businesses.

Ultimately, restaurants that focus on creating value — whether through great food, excellent service, or thoughtful use of technology — will continue to thrive. AI is just one more tool to help them do that.

About Bob Vergidis

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Today, Vergidis serves as the chief visionary officer of pointofsale.cloud and sits on the advisory board of the Interactive Customer Experience Association.

Bob has taught technology and lead change for a diverse list of clients including private companies, universities, the United States military and Fortune 500 organizations around the globe.  He launched one of the first knowledge-based incubators and founded an award-winning school for software development, e-media and design, as well as helped launch several companies and startups. Vergidis developed one of the first food mobile ordering solutions in 2000 and one of the first cloud-based point of sale systems. 

 

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