While news headlines obsess over AI destroying jobs, insurance industry veterans are sounding a quieter but equally troubling alarm: the technology could be erasing the informal training pathways and mentorship relationships that built professional expertise for decades.
Perhaps nowhere is this dilemma more acute than the disruption AI has already caused to the training of new insurance recruits. Automating relatively routine tasks like domestic policy quotes and renewals has created an unexpected consequence: young people entering the industry have lost their foundational learning opportunities.
“By automating that through AI, a couple of people in our broker community have said they've lost the starting point for young people to learn to understand policy,” said Richard Crawford (pictured, left), CEO of the Community Broker Network (CBN).
New technologies are bypassing the steps that, for decades, have taught the tools of the insurance trade. Without this hands-on experience, new brokers can struggle to explain to clients why they're recommending specific insurers or understand the reasoning behind coverage options. This leaves junior staff vulnerable to policy knowledge gaps and undermines the quality of advice given downstream.
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Michael Lewis (pictured, centre), cyber development manager for CFC Underwriting, expressed this widespread industry concern from an underwriting perspective. "Previously it's taken years to understand risk and be a decent underwriter,” said Lewis. “With these tools, processes will become more efficient, however we still need those fundamentals."
He advocates for updating training programs to ensure new entrants still grasp core risk principles and that AI is used as a tool rather than a replacement for understanding.
When junior employees spend their time monitoring AI systems rather than observing master practitioners at work, the intergenerational transfer of knowledge can slow to a halt. Colin Fagen (pictured, right), managing director at Blue Zebra Insurance, said there is another fundamental and old school way to remedy this technology issue.
“Sitting and learning from the older people in the industry, I think, has a lot of value,” he said. “In every role I moved into, I would often search for somebody who had the grey hair, who had a lot more experience than myself, sit near them if I could, and ask them questions.”
Fagen said it’s the nuanced and contextual understanding of how the industry operates – that can take decades to learn - that’s most under threat from AI.
However, under the pressure to reduce costs, some industry leaders worry that this growing training issue could be ignored.
"I think people may see it [AI] as an opportunity to drive cost out and that's all,” said Crawford.
This reductive cost cutting approach troubles many industry stakeholders who understand the importance of insurance requiring much more than mere transactional efficiency. The risk is that in pursuing automation for its own sake, firms may sacrifice the advisory quality and client relationships that differentiate professional brokers and underwriters from simple quote engines.
Crawford warned against allowing the industry to "dumb down the quality of advice by allowing AI to actually provide some level of general advice.” This trend could ultimately erode the value proposition that insurance professionals, brokers in particular, have to offer.
Over-reliance threatens to erode the communication skills and industry knowledge that differentiate experienced professionals.
“I think the fear for AI is that people become too reliant on it,” Fagen said. Insurance remains, fundamentally, a service industry where the ability to explain complex decisions to clients — especially unpopular ones — remains invaluable. When clients don't understand the decisions being made, trust erodes.
Lewis framed AI’s threat to the industry in stark terms: "I'm concerned for the people that haven't recognised that it is coming and haven't gotten around to it," he said.
However, Lewis and industry colleagues would agree that embracing AI technology needs to be done in a way that doesn’t leave an internal skills gap that ultimately undermines career longevity and business opportunities.
