The classic idiom, “there is no ‘I’ in team” isn’t part of Phil Sexton’s philosophy. In fact, on his team, the “I”—the individual agent—is everything.
Launching his Scottsdale, Arizona-based HomeSmart NEXT team earlier this year, Sexton drew upon his 20 years of technology and real estate experience to create the next evolution of the agent team, one where each agent is their own superstar, supported by AI-centric technology customized to their individual brand and business goals.
According to Sexton, agents didn’t get into real estate to be a cog in the wheel. “They got their real estate license so that they could build their own business. I’m just trying to empower that.”
Here, Sexton details how AI technology is helping him bring this modern-day vision of an agent team to fruition.
Maria Patterson: Phil, you’re taking a different approach to the traditional team structure. Tell us a little about it.
Phil Sexton: Instead of the last-name teams that are out there—where you’ve got some top producer that decides to bring agents on underneath them and generate leads for other agents that are on their team, and everybody helps build that last name—my goal was to be the backend support for the individual agents on our team. So collectively, we are a bunch of individual agents, and I’m the back-office support leveraging AI in order to scale my ability to assist all these different agents. I think that this business-services style of team, which is why I called it NEXT, is the next style of team that we’re going to see grow out there.
MP: You’ve been in the business a while, with stints at eXp and Realty ONE Group. What made you switch gears and affiliate with HomeSmart earlier this year?
PS: Because (our team) was so tech heavy, I wanted to align with a brand that was also tech forward. I’m always balancing the in-real-life versus virtual interaction with agents, so I liked that (HomeSmart) had offices. I like that they have a brand that is focused on technology, and I like that they provide me with the support and the autonomy to let me run this business the way that I want.
MP: Your team model feels more sustainable because it allows every agent to be their own individual superstar as opposed to agents eventually leaving a team because they want to go do their own thing…
PS: Exactly. From a marketing standpoint, my nemesis is the last-name team because they bring people on and they really don’t provide a path off. So agents get stuck with these golden handcuffs, and it feels like they have a job; and they didn’t get their real estate license to feel like they had a job. They got their real estate license so that they could build their own business. I’m just trying to empower that.
MP: You say that you’ve always had a ‘technology flavor’ to what you do. What do you mean by that?
PS: It started out of necessity. When I was the director of marketing for a local brokerage, there was nobody on staff that really dug into the efficiencies that could come with tech. So I bought a book from Barnes & Noble in 2006 on CSS (Cascading Style Sheets), which is a way to format websites. I started to figure out how to build websites in order to generate business, and I built an intranet for the company so that all 750 agents could come and look at the calendar online, and get all the forms they needed. Everything that they needed was now in the intranet.
That worked for the efficiency of the brokerage, but once I figured out how to use the internet to generate business, I started to get some notoriety around town and (I was asked to) speak and teach classes. When I was done, agents would come up and say, ‘oh my gosh, that was great, this is so wonderful,’ et cetera. But then very few agents would go and deploy the strategies that I just taught them. I witnessed that over the last 20 years of teaching agents about tech.
MP: So how did that experience inform the comprehensive AI environment you’ve now built for your team?
PS: When I saw this AI wave coming, I started getting involved. As I started to teach agents (about) what’s possible with AI tools, I knew that the majority of them weren’t interested in becoming AI experts. So I thought at the end of these classes, I need to have almost like a DoorDash button. When I teach everybody how to bake a cake, two people go home and bake the cake, the other 98 wish they had the cake. The DoorDash button at the end of the class means the cake just shows up if you don’t want to be the one to bake it.
That’s where this AI team model came from. All these things that I’m teaching agents about AI, I would like to just deploy on their behalf. So if they like the concepts and they don’t want to become an AI expert, then click the button—a.k.a., join the team—and now you’re able to leverage AI the way that I leverage AI. That journey started three years ago. That’s where I decided to build this AI foundation of a team, knowing that most people get into real estate because they’re people people, because they like houses. They don’t get into real estate because they want to become AI developers. However, AI can certainly help them with their business. It can help them stand out. And so that’s how this journey began.
MP: Did you build your own platform or are you working with a certain vendor? Are you utilizing HomeSmart’s technology?
PS: Yes, yes, and kind of. We are building our own AI tech. I am building apps that connect different data points to make the agent more efficient. And those are apps that I build custom for our team. And then in addition to that, I train our agents on how to set up their Claude or their ChatGPT so that they can use those interfaces that they’re familiar with. And then HomeSmart has been so receptive to opening up their systems and making changes and adjustments to their technology so that it works better with our technology.
HomeSmart is a critical piece because I really am not a fan of data input redundancy. A lot of teams out there will require that agents log business in their system, but then the agent also has to put all of the transactional data into the broker system. So the more I can use the data that the agent has to put into the broker system to power our systems, the better. I’m just excited that I’m at a company that supports that.
MP: You self-taught yourself on so many things, but for the average person, AI can be overwhelming and they don’t know where to begin. How do you determine what could be most effective for your team?
PS: I’m a trial-and-error kind of guy. We get bombarded in this industry with technology solutions. I have paid money for things that have proven to not be a good spend. The way that I view my team right now is as a proving ground. If there’s (technology) that comes across the plate that looks interesting, then let me find an agent that is interested in trying it. Once we try it for that agent, if we get results that are positive, that turn into business or turn into a better customer experience for their clients, then we deploy it to all the agents, and it turns into a training so that other agents understand how to adopt what we just built.
I never want an AI system to run without human interaction or human approval. They call those approval gates. I can build an AI system that can craft all kinds of wonderful things, but I don’t let those get deployed until there’s human eyes on it. And there’s two levels of human eyes right now. The first level is us here in the office. The system builds something that we like and that we think is good enough to go through our approval gate. Then the agent gets to look at what we’re doing and they get to have the final say. So those are human approval gates. We have those safeguards in place to make sure that the AI doesn’t run amuck.
MP: I love that. And I’m sure it helps your agents feel good about using AI. Do you run into situations where an agent is hesitant or a little bit frightened about AI?
PS: I’m fully aware of the trepidation that they might have. I’m a filter. I want to be able to filter out what is useful, what is beneficial, what is not going to ruin relationships, what is going to help enhance. My filter’s pretty thick in that regard. So by the time it gets through me, it’s because, “Hey guys, this is fricking awesome. We should do this, and here’s how you should connect your systems to this.”
With the different personalities on the team—we currently have 15 licenses that I’m working with right now—you have different levels of risk aversion. So the beauty of our system is that even though it’s run on a structured system, there’s personalized customizations that happen for each agent depending on how much or how little they want us to assist them.
MP: So clearly, you’re prioritizing human relationships…
PS: Agents have real human-to-human relationships that are sometimes fragile. They’re sometimes new relationships. For any human-to-human relationship to work, you need to have that personalized love and attention that goes into it. I don’t want AI to replace the personalized love and attention. I would rather have the AI prepare the agent so that they can provide better personalized love and attention to relationships.
MP: Is it fair to say that a client is really gravitating to one of your agents for the level of service they offer, and the AI is in the background just facilitating all of that?
PS: I’m not going to agree that it is only in the background because I think that AI, that new technology, is always something that people are interested in. I want our agents to let their clients know via their marketing that they’re not dated. The world has changed in the last three years, and I’m an agent that is on top of it, and I might even be an agent that is more on top of it than you’ve ever experienced before. So yes, it’s in the background to make (agents) better at the consumer-experience part, but it’s also in the front of some of the marketing that we do so that people can understand we’re not letting grass grow underneath us while the world is changing.
One example is interactive AI avatars. I can create the likeness of my agent where it looks and sounds like my agent, and I can feed it a context file relating to that particular property. Then on the QR code on the sign, instead of going to a landing page that’s static, it can go to a landing page that has the (AI) agent that pops up and says, “Hi, I am fully educated on this property. What questions do you have?” And now the consumer can interact with that avatar. Does that mean that that agent is going to sell more houses with that tech? Not necessarily, but does that show the public that this agent is at the forefront of what we’re doing? Absolutely.
MP: I imagine that the AI you’ve instituted for the team is giving everyone a tremendous competitive advantage, right?
PS: That’s absolutely the goal. There’s costs to all of these tools, and so another part of being the filter is, is this worth the expense? If it costs a whole bunch of money and it doesn’t turn into a better experience, a.k.a. more referrals or more business, then is it worth that monthly subscription fee? So we’re constantly evaluating that as well.
MP: Are consumers at a point where they’re expecting AI expertise from their agent?
PS: I now give consumers quite a bit of credit for understanding some of how to use AI. You’ve got to know what the limits are of the AI they use compared to the AI you use. A lot of times that (involves) the data sources that we have access to, blending data from different tools. So yes, the consumer knows a lot, but how we’re able to use similar systems with better data, I think still gives our agents an edge.
MP: So, what’s next? How do you possibly stay ahead of the rapid change in AI development so you continue to keep your team one step ahead?
PS: That’s the fun. Change is the constant in our business. Part of running any team, regardless if it was the team that I ran 13 years ago or the team that I run today, is where is this thing going and is there a first-mover’s advantage or do we want to watch other people on the bleeding edge make the mistakes, and then come in behind them with a system?
The coolest thing about AI right now is this shift away from what I call the mail-merge style of marketing, where we can remove and replace the first name, we can remove and replace the address, but all the messages are in a sense the same. Now that AI systems are able to review the history of that person, it can bring in a more personalized communication touch.
Every one of our agents has two filters that are built around them. I spend an hour with every agent when they come aboard, interviewing them on why they’re in the business, who they are, what they did before real estate, where they grew up, where have they lived, what do they do for fun, what do they want to be remembered by after a real estate transaction? That’s always custom to the human and that becomes a filter that we run any of their content through.
And then we create another filter that is their brand. Not everybody has to use Next branding. I mean, yes, HomeSmart Next is the entity that powers the agent, but it’s (the agent’s) brand, their color is there. And that’s a little bit counterintuitive to what a lot of teams are out there. I think a lot of teams want to be a consumer brand. I don’t want to be a consumer brand. I want to be a B2B brand where the agents know what HomeSmart Next is, but the consumer knows who the agent is.
