How Artificial Intelligence Transformed the Way This Team Trains Agents

Barry Jenkins was on the phone with a prospective buyer, trying to secure an appointment, as his whole team listened on. The buyer said he loved woodworking and wanted a house with a big garage where he could build furniture. Jenkins had some listings in mind, and after a few minutes, they agreed to meet at one in person.

However, they never did. Because this buyer wasn’t a real person.

The buyer sounded real over the phone, though, thanks to an artificial intelligence tool Jenkins installed in 2024 for his team of 80 agents in the Virginia Beach market. The tool, developed by a real estate tech company called MaverickRE, works with the Follow Up Boss platform, letting agents have realistic conversations with AI-powered leads. For Jenkins, the Chief Marketing Officer of Better Home and Gardens Native American Group, this new approach generated immediate results and reshaped the way his team operated.

A new way for agents to practice

When Jenkins first introduced the concept to his team, most agents laughed. Some were skeptical since AI’s rapid rise also brought on backlash as people wondered how the technology would impact real estate. 

But Jenkins showed them how they could customize the calls for buyers and sellers, and introduce objections. Also, he intentionally didn’t use the words “artificial intelligence.” He called it “a robot” instead. “AI is such an obscure, grandiose term,” he said. “Robot is like the personified version of AI.” He told agents to start calling this robot throughout the week to sharpen their skills and gameplan different scenarios. 

The team gave it a shot, mostly for practical reasons. Agents can improve to an extent by doing scripted role-playing with a boss or colleague, but there’s no great way for agents to consistently practice on demand and hear so many detailed responses at scale. Plus, with AI, agents don’t have to request time from a boss or colleague juggling other priorities.

Another practical benefit was that Jenkins could connect his custom metrics to the tool, then receive data on both AI calls and real client calls. For calls, the team focused on four internal metrics:

• Appointment asked
• Appointment date set
• Location collected
• Client motivation collected

The new data made it a lot easier for Jenkins to track team-wide trends and for agents to track their individual trends. For example, Jenkins noticed that only about 25% of intro calls to real people included a direct request to meet. So he made a request of his own: “If they have a pulse and a desire to transact, I want you to meet with them.” After a month of practicing with AI, agents were requesting to meet almost 70% of the time.

As agents got more comfortable with AI, their training evolved. Experienced agents who always hit their mark on the rubric could graduate, in a sense, from the tools. Then, if they needed one-off practice with seller leads, for instance, Jenkins could quickly set up a custom scenario for them.

For new agents, this training has become an essential onboarding resource. Jenkins asks every agent to make 30 robot calls during their first week and swears by the way it helps them establish good habits before they call real buyers and sellers.   

“I’ve never had anything move the needle with a new agent as quickly as this,” he said. “It’s really hard for them, but it’s a lot easier than calling 30 humans and getting yelled at.”

A new way for team leaders to coach

Jenkins is a busy guy. Aside from leading the Virginia Beach team, he speaks at conferences across the country and has written a book titled Too Nice for Sales. Additionally, he’s the Head Realtor in Residence for Ylopo, where he offers product guidance and helps advise clients.

These other roles helped Jenkins build connections and get unique access to this kind of new technology. But other commitments meant he was often short on time. Before implementing the AI tool, it got to a point where he wasn’t reviewing any team calls unless an agent had an obvious issue. Then he would pull up calls and retroactively go through a few recordings.

“I’m not proud of that,” he said. “Because of a lack of time, you had to be very specific.”

With AI, that all changed. Suddenly, he could pull up tailored reports on every call, and his agents could receive instant feedback. With just five minutes of looking at a report, he could notice a trend, walk into a sales meeting, and offer suggestions on how to handle a common objection.

This approach might sound unorthodox, but Jenkins can always point to the data to see whether the system is working. Aside from uncovering common objections, he can also measure how often agents overcome the objections, what percentage of the call the agent spends talking, and more. Interestingly, when more agents asked to schedule a meeting with someone on the first call, the share of leads who agreed increased from 42% to 49%. 

“I would not have seen that had I not had AI analyzing all my calls,” Jenkins said.

We’re still in the very early stages of seeing how real estate will apply artificial intelligence, but as the technology gets better, so should the use cases. 

“Soon my agents are going to be able to get a pop-up of me that uses training content to tell them what they should have done differently after a call,” Jenkins said. “Where we’re going with this is quite remarkable.”