Growth in real estate has always come with a built-in limit. If a team wanted to close more deals, it usually meant hiring more people to keep everything moving.
The problem? More agents required more managers. More listings meant more hours spent reviewing calls, tracking conversations, and coaching agents through the pipeline.
Shilo CEO Justin Benson believes that model is starting to change.
During a recent episode of the Knowledge Brokers Podcast, Benson joined Byron Lazine and Lisa Chinatti to talk about where artificial intelligence is actually showing up inside real estate businesses.
The conversation focused on the less visible parts of a brokerage operation, the systems that keep agents productive and deals on track.
AI-powered systems can now analyze sales calls, identify patterns in agent performance, and surface coaching opportunities without team leaders or managers sitting through hours of recordings.
For teams that rely on consistent training and accountability, that changes how leadership can operate.
What makes this shift more interesting is where it could lead.
Benson argued that the same technology now improving daily workflows could eventually allow service businesses like real estate teams to scale in ways that weren’t possible before, growing their operations without adding the same level of headcount along the way.
The hidden time drain inside most real estate teams
Most team leaders already know that coaching agents is one of the most important parts of running a productive sales organization.
The problem is the amount of time it usually takes to do it well.
Until recently, the only way to understand how agents were performing on the phone was to listen to call after call and look for patterns manually. That process worked, but it also created a bottleneck as teams grew.
Byron Lazine described just how time-consuming that process used to be.
“The amount of calls just a couple of years ago that team leaders and managers had to listen to, to get an understanding of where their agents were at in the sales process was obnoxious.”
That kind of manual review makes it difficult for managers to keep up as the number of agents increases. More agents generate more calls, which means more recordings to review and more time spent trying to pinpoint where conversations break down.
AI tools are starting to remove much of that friction.
Instead of requiring someone to listen to dozens of recordings, systems can analyze conversations automatically and surface the patterns that matter most. Managers can see where agents tend to lose momentum in a conversation, where objections appear, and where opportunities for improvement show up.
As Lazine explained, the result is a much faster feedback loop for coaching.
“And now, Shilo allows you to not even have to listen to calls. Just basically say, okay, this is where their average is on these calls. Here’s the mistakes they’re making in the summary.”
For growing teams, that means managers spend less time sorting through recordings and more time helping agents improve the conversations that actually drive deals forward.
Why AI could change the economics of real estate teams
The operational improvements Benson described go beyond saving a few hours each week. They point to a larger shift in how service businesses like real estate teams can grow.
By automating repetitive work and surfacing insights faster, the technology allows existing team members to handle more activity than they could before.
Tasks that once slowed organizations down, reviewing calls, tracking conversations, monitoring communication channels, can now be processed almost instantly.
That kind of efficiency changes the financial model of a team.
As Benson explained during the conversation, the gains go far beyond convenience.
“The productivity gains that will happen as a result for teams and real estate agents to become more profitable than they have ever been before is real.”
He went on to describe why this matters so much for service-based industries like real estate.
“Service-based companies will be able to scale further than they’ve ever been able to scale before, because they have the same kind of leverage that tech companies have now.”
In other words, the gap between tech companies and service businesses is starting to narrow.
Real estate teams still rely on people to build relationships and guide clients through transactions, but AI can remove many of the operational constraints that used to slow their growth.
For teams willing to rethink how their systems work, that opens the door to a very different kind of scaling strategy.
Why venture capital is suddenly paying attention to service businesses
One of the more surprising points Benson raised during the conversation had nothing to do with real estate specifically. It had to do with how investors are starting to look at service companies in general.
For years, venture capital firms focused almost exclusively on software companies. The reason? Software could scale quickly without requiring large increases in staff.
Service businesses worked differently. Growth usually meant hiring more people, which limited how fast those companies could expand.
Benson said AI is beginning to change that equation.
He pointed to a recent signal from one of the most influential startup investors in the world.
“Y Combinator just put out a request for startups for this quarter. They’re looking for service-based agencies to fund.”
That says a lot about how the economics of service companies may be evolving.
If AI allows organizations to automate more of the operational work that used to require human labor, those businesses suddenly become far more scalable. A company can serve more clients, process more activity, and grow revenue without increasing headcount at the same pace.
For industries built around service, including real estate, AI could give them the kind of operational leverage tech companies have enjoyed for years.
The human side of real estate isn’t going anywhere
Even with all the excitement around AI, the conversation kept returning to one reality. Real estate is still a relationship-driven business.
Technology can process information faster, automate repetitive tasks, and surface insights that would take humans hours to uncover. But it cannot replace the trust that buyers and sellers expect when they are making one of the biggest financial decisions of their lives.
Benson emphasized that the goal of AI should be to remove the work that prevents people from focusing on what matters most.
“If you can find ways to utilize AI to automate away the things that humans should not be doing and make sure that the humans are doing the part that the humans should be doing, which is connecting with other humans.
“We’re doing that to the nth degree over here. We’re not scaling down our client success teams or our service teams or sales teams or trying to replace any of that with AI.”
In other words, the real opportunity is freeing agents and team leaders from the administrative tasks that keep them away from clients.
Lisa Chinatti made a similar point when the discussion turned to what actually drives successful organizations.
“I think the one point that I want to make is that I think that there’s going to be this pendulum, right, where there’s going to be this heavy lean into AI and tech-based stuff because it’s new and it’s shiny and it’s sexy.
“But I also think that what we’ll see over time is that the humans pull back in wanting the human connection…. I think the three words that we need to be paying attention to are trust, culture and connection.”
Those qualities have always been the foundation of strong brokerages and teams.
AI may change how the work gets done behind the scenes, but the human side of the business still carries the most weight when deals are on the line.
What this means for real estate teams right now
The shift Benson described may still be in its early stages, but the implications for real estate teams are already becoming clear.
Many of the tasks that slow teams down today involve processing information rather than making decisions.
- Reviewing calls
- Tracking communication across platforms
- Identifying patterns in agent performance
- Managing internal workflows all take time.
All of these take time. And now, AI systems are beginning to handle those responsibilities faster and more consistently than manual processes ever could.
Benson gave a simple example from his own experience. In addition to building tools for real estate teams, he has created systems that monitor his own communication channels and surface the information he needs to respond quickly.
“I built my own little chief of staff that monitors my emails and Slack and Asana and all of these channels in real time and briefs me on things and then texts me when things need to be responded to.”
For real estate teams, that kind of automation can remove many of the small operational barriers that add up over time.
- Managers can spend less time reviewing data and more time coaching agents.
- Agents can focus more energy on conversations with clients instead of administrative work.
The result is not a fully automated business. That’s not the goal.
Instead, it’s a more efficient business, where technology handles the background work, and people spend their time where they add the most value.
