MGAs should measure AI ROI by speed to revenue

The AI opportunity is getting bigger. So is the list of places you could put it to work. The challenge is deciding which investment will actually move the business forward.

According to a 2026 McKinsey report, one in five respondents said their organization was limiting AI use because of operating costs. But looking ahead, 60% expect their organizations to increase AI investments over the next year. As investment increases and AI becomes a larger part of day-to-day operations, how organizations put that investment to work needs to become more strategic. 

For MGAs, that means focusing on opportunities directly connected to growth, including increasing the capacity of existing teams, helping them pursue and win more business, and getting new opportunities to market faster. Those outcomes can provide a much clearer picture of the real return AI is creating.

Focus on the team you have

Increasing capacity starts with helping the people already on the team accomplish more. Underwriters bring expertise, judgment and relationships that technology cannot replace, but too much of their time can be consumed by administrative work and manual handoffs. When AI removes some of that friction, the return is not simply time saved. It gives underwriters more time to apply their expertise to the work that can generate business.

There is a longer-term return as well. Critical knowledge about underwriting, workflows and relationships often lives with individual employees rather than in accessible data or standardized processes. AI can help capture and organize that institutional knowledge, so it remains available as teams change and experienced employees retire.

For MGAs evaluating AI return on investment (ROI), the value of their people should be part of the equation. AI can create value today by giving underwriters more capacity, while also helping preserve and extend the expertise the business will need tomorrow.

Underwrite the business you can win

Earlier this year, I heard a customer say, 'This company is releasing 15 new AI agents.' It sounds impressive. But my first question was, how many of those 15 will actually be valuable to your business? 

For MGAs, there is a fairly standard underwriting workflow, and not every step in that workflow needs an AI agent. The bigger opportunity is identifying the critical points where AI can help an underwriter get to the right business faster. That could mean helping teams prioritize the opportunities most likely to bind, reducing the manual work that slows down a viable submission, or getting clear information in front of the underwriter sooner.

That is a much more meaningful way to think about ROI than counting how many AI capabilities an MGA has deployed. The value comes from how well those capabilities perform at the points that matter most to the business. If AI helps underwriters spend more of their capacity pursuing opportunities they are positioned to win, the return can show up in more business written and stronger profitability. 

For MGAs, success is not about having the most AI. It is about putting AI where it can help them adapt faster and grow smarter.  

Make speed part of the value equation

MGAs are constantly evaluating new markets and specialized programs, but identifying an opportunity is only the beginning. Once an MGA secures carrier capacity, it still needs the technology and workflows in place to start writing business. 

Consider an emerging risk where customer demand is developing quickly, such as new exposures created by data centers, for example. An MGA may identify the opportunity and secure carrier capacity, but it still needs to build the underwriting workflow, configure the supporting technology and get distribution ready before it can begin writing business. If AI can compress that work, the MGA can move from identifying an opportunity to generating revenue faster.

That changes how MGAs should think about AI ROI. The return is not limited to the cost of using AI to complete a task or the hours of manual work it removes. It can also be measured by how quickly an MGA can turn an opportunity into revenue. 

When speed can determine who gets to a market first, the real ROI from AI may be less about what the technology helps an MGA save and more about what it helps the business capture.

Make every AI investment count

AI has real infrastructure and operating costs, which makes it even more important for MGAs to be deliberate about where they invest. Before adding another AI capability, leaders should be able to identify the business outcome they expect to improve. 

For example, if 500 submissions come in, an underwriting team may not realistically have time to give each one the same level of attention. AI can help surface the opportunities with the strongest likelihood of turning into business, so underwriters can focus their limited time and judgment where it can have the greatest impact. 

Cost efficiency should remain part of the evaluation, but it does not have to be the deciding factor. The goal is not to find every place an MGA could use AI. It is to identify the places where AI can materially change what the business is capable of doing and then measure whether it actually does. That is where MGAs will find the real ROI in AI.