Small Brokerages Won’t Be Left Behind
You don’t have to be a large firm to implement AI in a manner that generates significant benefits at a reasonable cost, as the experience of one smaller brokerage shows.
StreetSmart Insurance, with eight agents and brokers, has applied artificial intelligence to its operations since late 2024.
The Freehold, New Jersey, firm has put AI to work for a variety of middle- and back-office functions, says Chief Operations Officer Carlo Ferrara. That toolbox encompasses reviewing policies for accuracy, comparing quotes for exclusions and covered limitations, and enhancing the company’s telephone system to convert messages into emails on coverage issues that can be more easily processed by the back-office team.
Costs for each solution vary, but StreetSmart now spends approximately $1,750 per month for the suite of tools.
“People complained about my phone system, so I was like, ‘I have to have a solution for this,’” Ferrara says. “And the quoting was taking a little bit long, so we need to come up with a solution for that. And then I use [AI-driven insurance policy analysis software] Qumis myself a lot when I’m comparing policies. My staff is relatively younger, and for them to have a tool like that at their fingertips is super valuable.”
That doesn’t mean the technology was easily implemented; the options were largely inexpensive but time-consuming to make operational or expensive but not requiring significant training, Ferrara says. “We took the first approach as [full functionality of] AI is not there yet, and we wanted to give feedback by working with up-and-coming vendors that do not have a lot of clients and are willing to craft it the way we want to use it.”
While the company rejected some AI solutions, others quickly proved their value. Ferrara highlights a quoting tool by Gaya AI that he says will reduce contractor headcount and improve turnaround speed by roughly half by pasting quotes from carrier websites into internal documentation. The Qumis policy checking tool reduces the time that would otherwise be spent manually checking policies by 30%, Ferrara says.
This approach comes with challenges, he acknowledges. Top of the list is understanding how AI will fit into an agency’s workflow, including whether staff will use it. Some staff at StreetSmart still do not use all the tools.
But not investing in AI was not an option, Ferrara adds: “Try it out on your agency, or your competition will.”
