Three Steps Wealth Managers Should Take Before Adopting AI Tools
Many wealth management professionals have experimented with AI tools but haven't seen the results they expected. A minority have figured out how to use AI effectively-and their approach differs in three concrete ways.
Steven Miller, chief operating officer of Focal, an AI platform for Canadian financial advisors, shared these distinctions at the ETF & Investment Forum in Toronto this month. His advice applies to any firm considering AI adoption.
1. Define the specific problems you want to solve
Firms often claim AI will make them "more efficient," but that's too vague to act on. Miller said organizations need to identify which problems are worth solving and understand their magnitude within the business.
Ask three questions: What problems exist? What does success look like? What guardrails does the solution need?
"You would be surprised that a lot of people don't have a good answer to this question," Miller said. Since wealth management operates in a regulated industry with firm-specific workflows, AI tools must work within those constraints.
2. Build your data infrastructure first
Before deploying AI, firms need accessible, structured data. Miller met advisors storing client notes on paper-a situation where current AI tools can't help. Those notes need to move into a customer relationship management system first.
Workflow design matters equally. Many firms have used the same processes for years, and AI can introduce radically different ways of working. That requires retraining staff and time for adjustment.
Avoid the trap of using AI in every task. Miller said: "Just because you use AI a lot doesn't mean you get better outcomes." Instead, align AI deployment with specific goals-improving client experience or reducing back-office hours-while maintaining regulatory compliance.
3. Decide whether to build or buy
Most firms lack the engineering resources to build custom AI tools. Miller said the successful approach is building strong data foundations internally, then selecting best-of-breed tools from different vendors.
This "marketplace hybrid" gives advisors flexibility to choose tools that solve their actual problems while giving leadership visibility into what works.
When evaluating vendors, check three things:
- Does the engineering team have a track record building in regulated financial services? Some vendors have been investigated by the Office of the Privacy Commissioner of Canada for privacy violations.
- Does the vendor understand provincial regulatory variations?
- Does the service-level agreement guarantee your data won't be used to train large language models like OpenAI's?
Vendors should not store video or audio recordings within their platform, as this risks violating client privacy.
Why advisors remain essential
When asked whether AI and robo-advisors threaten advisor jobs, Miller said the opposite will happen. As Canadians age, start families, and build businesses, their financial needs grow more complex. They'll need advisors more, not less.
AI handles routine work. Advisors provide judgment, wisdom, and relationships-things AI cannot replicate. When AI produces wrong answers, clients will turn to advisors who understand both the technology and the client's full situation.
For management professionals implementing AI, the stakes are clear: understanding how to select and deploy AI tools directly affects both productivity and client outcomes. The firms that get this right will see measurable improvements in both.
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