Pizza Hut has updated its technology with AI to better analyze customer needs.

Pizza Hut Plans to Rely on AI as Its Way to Stay Ahead Of Competitors

When you are sitting in the number one position of an industry that is projected to reach $126.91 billion in sales this year, then you are feeling pretty good. But if you want to stay in the top spot you need to keep up with what your competitors are doing. In fact, you need to evaluate what your own company is doing. Especially when it comes to the optimal use of AI and machine learning.

The company referenced above, Pizza Hut, was featured in a story on, written by Sage Lazzaro Burns. In an interview with Tristan Burns, Pizza Hut’s global head of analytics, he gives several insights into what Pizza Hut is thinking these days when it comes to staying number one in the market. One interesting mention was how Pizza Hut looks at data for each individual customer, including what the current weather is at their house when they order online.

Did you know they were the first franchise in the country to have online ordering for pizza? But they didn’t stay in step with the very technology that gave them such an advantage. Their competitors like Dominos did, and captured a huge part of that original Pizza Hut customer base.

Now Pizza Hut wants to build its own analytics, data gathering, and the use of AI to enhance its bottom line. To find out more about the company’s approach to data, its partnerships, and why it chose “build over buy” for its machine learning technologies, read the entire interview. According to Burns:

“Now Pizza Hut Digital Ventures, the organization I work for that is specific to Pizza Hut International, is taking a tech-first approach to redesigning, reimagining, and recreating our ecommerce capabilities. We’re in the process of building and scaling out some pretty robust solutions. It’s a very, very data-centric and very customer-centric approach.”

Later in the interview, Burns said this is just the start of the merging of Pizza Hut and AI.

“We’re in the early stages of an AI journey. And part of our machine learning program is to ingest customer behavior and a little bit about who customers are, where in the world they are, what the weather might be at their location, and then surface relevant product recommendations to them during their experience. We’re still early days in that process, but we’re building in-house capabilities to own it and with the hope that we can do a better job and have more specific outcome.”