Recent graduates are significantly more open to using AI for insurance research than the general Canadian population, but that openness hasn't translated into trust in the technology's actual recommendations, according to new research from Securian Canada. The gap matters because this group is making major financial decisions alone for the first time, often without the support structures older buyers rely on.
Securian Canada's research found that 38% of recent graduates are either already using AI for insurance-related research or would consider doing so, compared to 26% of Canadians overall. That willingness drops off sharply when it comes to actually trusting the results.
"About 23% would trust it, compared to 21% of the broader Canadian population," said Nigel Branker, CEO of Securian Canada. "So openness to usage is higher, but trust on recommendations is comparable, and not high."
Why recent graduates are different
Branker said the pattern fits a broader theme across underserved groups Securian Canada has studied, including gig workers and newcomers, who tend to value financial protection highly but face real barriers to getting information and advice. Those groups are increasingly turning to self-serve digital tools because traditional channels haven't served them well, he said.
Recent graduates stand out within that group because so many are navigating these decisions entirely on their own. "Two-thirds of recent graduates are single compared to 28% of Canadians overall," Branker said. "And that means that 61% of them make decisions independently. So there's a lot of first-timers making decisions, and making them on their own."
Experience changes trust levels
Prior experience with AI appears to be the biggest factor separating graduates who trust its recommendations from those who don't. Trust roughly doubles among recent graduates who have previously used AI for insurance research, compared with those who haven't - a pattern that also shows up across other demographic lines, including a gap between men and women.
"We do see the trust increases to about 44% if people have used it previously for insurance recommendations," Branker said. "That's for recent grads, and that compares to about 28% for the broader population." That's a strong signal for AI for Insurance applications, though Branker cautioned that experience alone doesn't solve the technology's limits.
"It doesn't always distinguish between credible expert guidance and less reliable sources," he said. "We definitely encourage Canadians, and especially this segment, to use it responsibly in their planning, but also use critical thinking and trusted advice."
Where AI falls short
Branker illustrated the technology's limits using a trip-planning analogy. Asking an AI tool to plan a trip to Italy will produce a polished itinerary in seconds, he said, but a more useful result depends on the traveller first providing detailed context about their own preferences.
"In a travel instance, the smarter way to use it is to say, well, you should ask me 20 questions about what do I like to do on a trip. Am I active? Do I like food? Do I like beaches?" Branker said. "I think a lot of people stop at the first level."
The same gap holds for insurance decisions, where context matters deeply to the outcome, noted Branker. That's also why Securian Canada sees AI as one part of a broader financial plan rather than a substitute for human advice, and why the company is redesigning products around the barriers younger, independent buyers face today - such as the friction of requiring an in-home nurse visit for basic underwriting. For research workflows, AI can help users explore scenarios, but it can't replace judgment.
Why this matters for insurance professionals
For insurance professionals, the split between usage openness and trust points to a clear opportunity: buyers are already testing AI tools and learning that the output depends heavily on what they put in. That creates a role for advisors who can get clients to explain their actual circumstances - and who can teach clients which questions an AI tool should ask them before it produces recommendations. Simplifying product design and underwriting friction, the way Branker described, could draw a generation of independent buyers to move from researching to purchasing decisions, thanks to professional guidance.
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