How Raymond James Canada uses AI to free advisor time
Raymond James Canada is implementing the FNZ platform in a move that will make it the second FNZ customer in Canada after BMO. The current plan is to go live roughly six months after BMO’s scheduled early-2028 launch.
What makes the programme significant from an AI standpoint is not the platform switch itself but how AI will be woven into it. “When I’m talking to advisors about what’s coming, it’s less about, hey, you’re going to use an AI thing,” Newton says. “You’re using the platform and AI is sort of embedded. It’s in the DNA of the platform itself.”
The goal is that advisors benefit from AI capabilities without needing to know they are using them. Post-migration, the platform is expected to surface nudges, next-best-action prompts, and data-driven insights drawn from an advisor’s full book of business. The longer-term vision is cross-functional AI automation spanning front-office advisors, compliance, and operations.
Managing adoption across a mixed advisor base
Newton is candid about the adoption challenge. The average age of an advisor at Raymond James Canada is 55, and the firm is managing two very different cohorts at once. One group is cautious; not necessarily resistant to change, but carrying a heavy load of regulatory demands and new technology alongside the task of running their own businesses. The other group is all in. “They want Raymond James to implement this stuff faster,” Newton says. “I need this yesterday.”
The challenge, as Newton frames it, is that AI is not really a technology to be trained on but a skill that requires a change in behaviour. And those AI capabilities are themselves moving targets. Something that failed in Copilot two weeks ago may work today as Microsoft and the underlying models continue to improve, which makes point-in-time training quickly outdated. “So it becomes a challenge when we’re trying to roll out some of these tools,” he says.
