"Imagine if you went to a coffee shop every day for 100 days, and the barista didn’t remember your order," says Mark Austin, Vice President of Data Science and AI at AT&T. "You wouldn't feel very good, right? Our customers are the same way."

The disjointed nature of customer support has long been a pain point in the telecom industry. Users often engage across multiple channels—browsing online, calling a support center, or visiting a retail location—and are frequently forced to repeat their needs or explain their history at every new touchpoint.

To tackle that first challenge—getting the customer to the right place without forcing them to navigate frustrating phone trees—AT&T uses BigQuery. Within its contact centers, accurate initial routing is everything. By deeply analyzing customer history to understand exactly why a person is reaching out, BigQuery provides the intelligence AT&T needs to bypass rigid menus and direct users to the right solution or specialized human agent in seconds.

This means that if a customer pauses a purchase online, walks into a physical retail store, or calls back weeks later, the AI remembers exactly where they left off. It knows if they were looking at a specific device or if they qualify for a military discount. Customers never have to repeat themselves. Instead of starting every call from scratch, the AI picks up the conversation, creating a personalized experience that gets the customer what they need, faster.

As AT&T continues to refine these agents—ensuring they remain secure and closely monitored—the company is preparing to deploy even more advanced voice capabilities. Ultimately, this frees up AT&T’s Customer Care agents to focus on more complex customer needs and proactive customer-focused strategies while driving about $150 million in annual savings.