AI is squeezing entry-level tasks. RBC Wealth Management sees a path to stronger advisor talent
AI is taking over a big share of entry-level work. That's where many advisors traditionally cut their teeth. The risk is obvious: fewer entry roles, thinner benches, and a weaker pipeline. RBC Wealth Management Canada's Head of Training & Development, Natacha Savard, is taking the opposite view-use AI to free people for client time and build better advisors from day one.
What the data says
Studies cited by global forums estimate that AI could replace over half the tasks done by market research analysts and an even higher share for sales reps, while managerial work is less exposed. Hiring of new graduates in the US has cooled, a trend reflected in federal data on openings and hires.
The talent question for wealth management
Many advisors start as bank tellers or call center reps. If those roles shrink, how do you train future advisors? Savard's answer: recruit directly, train intentionally, and let AI remove low-value tasks so junior talent can learn where it matters-the client.
RBC WM's approach
"The intention is really, to find efficiencies on things like administration, summarizing meeting notes and research reports. If we find those efficiencies, I think it allows people to spend more time with the client," Savard says. "I don't know that it will replace jobs. I hope it makes the jobs less administratively heavy and gives us an opportunity to hire talent that's more client facing."
RBC Wealth Management is investing in AI to evolve roles, not erase them. The firm recruits directly from universities and runs the long-standing President's Club program, bringing in roughly 100-125 new advisors each year for decades. The goal: more client exposure, less busywork.
What AI should do-and what it shouldn't
- Do: automate admin-meeting note summaries, research digests, CRM hygiene, scheduling, call logs.
- Do: accelerate prep-draft client follow-ups, outline proposals, highlight risks for review.
- Don't: replace client relationship work. With high net worth clients, trust and judgment are the job.
- Don't: run unsupervised on advice, suitability, or product recommendations.
Savard is clear: bots can cover website chat and some call center tasks, but even junior associates build trust face-to-face (or screen-to-screen). Complex households need empathy and practical judgment that a model can't provide.
A practical playbook for managers
- Redesign the "entry role" into an Associate Advisor track. Make the first year 60-70% client exposure (shadowing, co-meetings, follow-ups) and 30-40% AI-assisted ops.
- Pair AI with apprenticeship. Shadow calls, debrief every meeting, and turn AI notes into coaching moments.
- Set AI-use standards. Where to use it (notes, emails, research), where not to (advice, suitability), and what requires sign-off.
- Build training in three lanes: client communication, planning fundamentals, and compliance/ethics. Add short modules on prompt quality and verification.
- Choose a small, safe tool stack: meeting transcription/summarization, research synthesis, email drafting with approval, service triage. Enable audit trails.
- Recruit for entrepreneurial drive. Advisors are business builders; hire for initiative, resilience, and learning speed.
- Protect client data. Mask PII, restrict external calls, log prompts/outputs, and route sensitive work to firm-reviewed models.
Metrics that matter
- Client hours per week per associate (trend up).
- Admin minutes per meeting (trend down).
- Time-to-first-book and ramp productivity.
- Quality: CSAT/NPS signals, compliance exceptions, error rates.
- Talent: 12-24 month retention, promotion velocity, pipeline health.
Recruiting an AI-native cohort
New graduates expect solid tools. Savard points to RBC's investment in its own generative AI (including Borealis AI) as a draw, but she doesn't lead with the tech. She leads with the human side of the business and shows how AI supports that mission.
RBC's brand helps, but Savard says the industry still has a visibility problem. Many business students can list investment banking roles, yet they've barely heard of wealth management. Education and exposure fix that.
What to do next
- Map your top 10 repetitive tasks and automate three this quarter.
- Stand up an Associate Advisor cohort with clear client-facing goals and a named mentor for each hire.
- Publish a one-page AI policy and a simple review workflow for AI-generated client communications.
- Report monthly on the metrics above. Adjust training based on the data.
The entry-level floor is changing. That can stall your pipeline-or it can speed it up. Savard's approach shows a simple path: give juniors more client time, give them better tools, and keep the human relationship at the center.
If you're assembling an internal learning path by job role, this catalog can help: AI courses by job. For teams in finance, a curated tool list is here: AI tools for finance.
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