How AI can drive and bridge the insurance skills gap

Artificial intelligence presents an opportunity to bridge a skills gap between older, more tenured insurance professionals and the younger counterparts the industry often struggles to recruit, according to new insights from PwC.

Marie Carr, global growth strategy leader, PwC, told InsuranceNewsNet that AI is reshaping the way talent is developed in the workforce.

“A number of folks immediately justify AI investments by saying, ‘Hey, here’s how we can make things faster, better, use fewer people and we don’t know what’s going to happen to the junior people because they’re normally doing that repeatable thing that’s going to go away,” she said.

“We started to step back and say, ‘Well, no, this is actually a wonderful opportunity for you to rethink and revisit how, exactly, you are developing your skills in your organization.’”

Bridging the AI skills gap

While AI is often framed as the biggest source of tension between older and younger generations of insurance professionals, Carr said it actually represents a perhaps-overlooked opportunity for more meaningful coaching, upskilling, leadership building and knowledge retention.

She noted that, in many cases, more tenured professionals have a lot of intuition, knowledge and critical thinking developed from years of experience. While that agent or broker may not know how to build a GPT, they have invaluable insights they can bring to the table — and AI, perhaps counterintuitively, is precisely the catalyst Carr believes can help wield that knowledge.

“One of the advantages of AI, if we really look at it from a skills perspective, is that it allows those things which are experiential. Having experience brings the cognitive piece. It brings the separating fact from fiction, as I like to call it, to the table. And so, I think that tension turns into a bridge. I think it now turns into an opportunity for some who are going to lean in and accelerate growth,” Carr said.

This can be done by putting experienced employees in the AI loop, such as having them be mentors to younger staff so they can not only provide coaching, but at the same time also learn tech skills from their juniors.

Carr noted that, when people begin to use AI for underwriting or claims adjusting, they may “jump in without any experience and use it without thinking about it, and they don’t challenge the recommendations that come out.” Similarly, for more complex cases, they may not really know how to deal with it.

“However, if you have a human in there and then if you match that human with even more seasoned people, what you now have is a wonderful coaching opportunity where that person now can say, ‘Here’s what you’re missing,’” she said.

The leadership, mentorship and knowledge-retention opportunities created through AI adoption “can’t quickly be codified when people are building their AI models and GPTs,” Carr noted, emphasizing the value of keeping humans in the loop not just for guardrails to AI output but to facilitate twofold upskilling.

“The bridging that happens is if you put the experienced people in the loop, you create an opportunity where you are getting them up the learning curve faster,” she explained. “You are capturing those opportunities where they can understand more deeply what makes them expert, what’s that company’s secret sauce. Pairing the emerging talent with the senior experts is a better, more modern learning model.”

This, in turn, helps to ensure centralized institutional knowledge is available to everyone and the organization has the highest quality, she said.

Rethink, not replace

According to Carr, tech leaders in the insurance field look at AI as a way to reimagine talent development and skills training rather than an opportunity to reduce staff.

In her opinion, although AI has become capable of handling repetitive tasks and even making recommendations to get agents started, “the complexity of insurance, no matter what we’re talking about, is not yet at the point where you can just turn all of it over to AI agents.”

PwC recently published insights identifying “loss of human expertise” as a “potential downside to AI systems,” stifling crucial opportunities for “workers to develop the skills” that are needed.

“Those who are starting to play with that differently are beginning to say, ‘Maybe I’m going to give staff more responsibility. Maybe I want to reimagine how this process goes. Maybe I want to change the way in which I am training and developing so that I can get more out of it,’” Carr said.

For example, she said, one leader reportedly weighed shifting away from a vertical tenure and time-based model to one based on skills development in the wake of AI.

“AI is allowing us to challenge the models of how we develop people, and I  think those who lean into it the right way will create space between them and their competitors,” Carr said.

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