Artificial intelligence is redefining workflows in insurance – streamlining everything from actuarial calculations to client onboarding. But as machines take over more of the foundational tasks once assigned to junior professionals, a key question is emerging: how will the next generation build the expertise they need?
While expert knowledge is difficult to scale or automate, many tasks performed by junior roles can be, which can create a mentorship gap in the future.
“It's very hard for us to replicate 30 years of insurance knowledge that an insurance executive has, but when you think about the work traditionally done early on in insurance careers, there are pieces of that that can absolutely be automated,” said Laura Doddington (pictured left), head of personal & commercial lines consulting and technology for North America at WTW.
Doddington said the transition raises concerns about how talent will be trained without access to the manual tasks that once served as on-the-job learning.
“I don't think we’ve quite worked out how to bridge that learning gap,” she said.
While she believes roles like underwriting will still require human expertise – even at junior levels – others, particularly in actuarial, may be reshaped entirely by automation.
Jordan Aravena (pictured right), relationship manager at FIRST Insurance Funding of Canada, echoed the importance of mentorship – not just in response to AI, but also in light of broader shifts in how brokers and insurers operate post-pandemic.
“I would love to see more emphasis on mentorship and recruitment of new talent into the industry,” Aravena said. “There are many professionals in our industry right now that are looking to retire or sell their business in the coming years, and it's going to create a significant talent gap.”
Remote work, she added, has also made traditional mentorship more difficult.
The shift to remote work over the last five years has also created challenges with the knowledge transfer and mentorship, she said.
“It can be really challenging to learn over a screen, right? I think being able to get up and walk over to someone's desk is crucial to be able to grow.”
In distribution roles, AI is not expected to replace brokers, but rather to serve as a tool that enhances how they assess and communicate risk. According to Doddington, brokers – as well as call center and client-facing staff – will benefit from access to richer, more organized information.
In commercial lines especially, she says that automation can surface detailed histories, portfolio exposure data, and other key insights that enable brokers to make better-informed decisions when structuring placements. But while AI may strengthen their understanding of the risk, it won’t eliminate the need for human judgment.
“I don't think it takes away from the need to then have somebody take the insights into account to provide a risk-adjusted advice,” Doddington said.
Aravena emphasized that brokers still require guidance – even if the tools at their disposal are more advanced than ever. As AI takes over repetitive administrative tasks like data entry, young professionals can now focus on more client-facing responsibilities earlier in their careers. But this acceleration, he said, makes mentorship even more critical.
If junior brokers are properly mentored, Aravena believes they are well positioned to thrive in the current environment.
“They can generate revenue even faster. They get to manage these clients even more efficiently, using their time for revenue generating activities versus administrative tasks … and grow a bigger book quicker and with better retention than they might have been able to 20 years ago,” she said.
As AI tools become more embedded in day-to-day insurance operations, firms are beginning to retrain employees to work with these new systems – but broader, long-term strategies for mentorship and skills development remain underdeveloped.
Doddington pointed to AI-powered claims triage as an example where retraining is already underway. Claims handlers are learning how to interpret and act on system-generated insights, rather than manually assessing each file from scratch.
However, she cautioned that the industry hasn’t fully considered what’s lost when junior employees no longer learn by doing.
She also sees growing demand for consultants who can help companies not only deploy AI tools but build the governance, training, and support systems needed to make those tools effective – and safe.
“In some areas, that retraining is already underway, but we are not yet thinking holistically enough,” she said.
