AI Automation Puts Women’s Insurance Roles at a Crossroads

AI’s effect on women in insurance may turn less on which tasks it can automate than on how insurers use the capacity automation creates. At the Business Insurance Women to Watch Leadership Conference in Chicago, speakers urged companies to improve work and preserve expertise, while employees build skills and relationships that can help them adapt. That distinction matters because a tool can remove steps from a job without reducing the pressure on the person doing it. The result depends on decisions made after the software takes over a task.

Women perform a disproportionate share of administrative work in claims and underwriting, said Michelle Raue, founder of Nashville-based Raue Strategic Advisory. As AI takes on repetitive tasks, employees could spend more time with policyholders. That human contact matters during claims, she said: “People have a loss, and they want to tell a human about their loss.” A claim is a process, but it’s also an interaction with someone dealing with a disruption. If automation gives employees more time to listen, explain next steps and handle complicated cases, customers may notice the difference.

That benefit isn’t automatic. A system may speed up routine work while leaving employees responsible for reviewing outputs, resolving exceptions and managing customer expectations. Insurers will still need people to judge when a case doesn’t fit a standard pattern. The technology’s practical value will depend partly on whether companies account for that work when they redesign roles.

Automation’s productivity test

Removing routine tasks won’t necessarily reduce workloads. Ema Roloff, cofounder and chief growth officer of Madison, Wisconsin-based Roloff Consulting, said previous technology shifts have often added work instead of freeing employees to focus on higher-value responsibilities. A new system can change the shape of a job without making the job smaller. Employees may spend less time entering or transferring information and more time checking results, handling exceptions or meeting higher expectations for throughput.

“What we are seeing a lot of happening is the manual repetitive work being taken away, and instead of opening up capacity for what most people would see as the more important work, we’re shoving more work onto people’s plates,” she said.

That pattern has consequences for insurers as well as employees. Roloff said companies that focus too heavily on eliminating positions risk losing people who understand their operations and customers. Such knowledge can be hard to capture in written procedures: experienced staff often know which details need closer attention and how a customer’s circumstances affect a conversation. If that understanding leaves with employees, faster processing may not translate into better decisions or service.

As AI handles routine work, industry knowledge, communication and relationship-building may become more valuable, Roloff said. This is more significant than it looks. Automation can make a task easier to perform while raising the importance of judgment around it, especially when information is incomplete or a customer needs an explanation. The employees best positioned to contribute may be those who can connect a system’s output with the realities of a claim or underwriting decision.

For women whose roles include automatable tasks, the transition could bring greater displacement risk. But whether automation yields better service or simply more work will depend in part on how employers redesign jobs and allocate the time saved. If the saved time is treated only as room for higher volume, workers may see little improvement in their day-to-day responsibilities. If you're working in this space, the useful question is what the job will ask you to do after the repetitive steps are gone.

Skills and sponsorship

Heavy workloads can leave employees little room to experiment with AI, Raue said, making access to training important. She encouraged women to seek learning opportunities through their employer or independently. “If your company’s not offering you opportunities to learn in that space, go out and learn them yourself because you’re going to need them and you’re going to make yourself more valuable that way,” she said. That advice puts responsibility on individuals, but it also points to a constraint: learning takes time, and time is precisely what overloaded employees may lack.

Training is most useful when it helps employees understand how a tool fits into their actual work. Knowing how to operate software is one part of adapting; recognizing when an answer needs review and communicating the result to a customer are different parts. Employers have a role in making that learning possible within the workday, especially if they expect staff to take on new responsibilities as automation expands.

Raue also warned that resisting AI outright could increase the chance of replacement: “The more you fight it, the more they’re going to try to replace you with it.” The warning is blunt, and it reflects the pressure employees may feel as companies assess what work can be automated. Still, adoption alone won’t guarantee security. Workers need a chance to build skills that complement the system, while employers need to decide whether those skills will be recognized and used.

Career networks and sponsors can help women navigate change, said Lorene Phillips, founder of Bermuda-based consultancy Clarendon Wallace. She advised building professional relationships before a career shift is urgent and seeking senior leaders who will advocate for advancement. “If you don’t have one, find one. Search for one, but you need one,” Phillips said. A sponsor can make an employee’s work more visible to decision-makers, while a wider network can offer perspective on how roles are changing. Those relationships don’t remove the uncertainty, but they can help women find opportunities as responsibilities shift.

What insurers do with the time

For insurers, the measure of AI’s value will be whether it gives employees room to serve customers better while retaining the experience those relationships depend on. The conference speakers’ comments point to an organizational test: companies must decide whether productivity gains will support more careful service, greater workloads or fewer positions. Those choices will shape the effect on employees as much as the technology itself.

And yet, the outcome won’t be visible in a software rollout alone. It will show up in how claims are handled, whether employees can explain decisions and whether experienced staff have reason to stay. Here’s the thing: efficiency is easy to describe, but the quality of the work that remains is harder to measure. The human part. That’s where insurers will have to show what the saved capacity is actually buying.