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Canadian Wealth Managers Lag Behind Global Peers in AI Adoption

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  Published in Business and Finance on Wednesday, December 3rd 2025 at 20:01 GMT by The Globe and Mail
      Locale: CANADA

Canadian Wealth‑Management Firms Lagging Global Peers on AI Adoption, Study Finds

A recent industry survey has revealed that Canada’s wealth‑management sector is falling behind its international counterparts when it comes to the deployment of artificial‑intelligence (AI) tools. The research, commissioned by the Globe and Mail in partnership with a leading financial‑services consultancy, examined the extent to which firms across North America, Europe and Asia are incorporating AI into core business functions such as investment research, portfolio construction, client service and risk management.

The Study at a Glance

The study surveyed 236 wealth‑management firms worldwide, covering a range of firm sizes—from boutique advisors with a handful of advisers to global platforms that manage billions in assets. The respondents were asked to indicate whether they had adopted AI solutions in specific areas and, if so, to what extent those solutions were integrated into day‑to‑day operations. The survey was published in a full‑length report available on the consultancy’s website (see the “Full Report” link in the original article for detailed methodology).

Key findings include:

While Canadian firms are on the rise in AI usage, the overall adoption rate lags by 15‑20 percentage points in most categories compared to the United States and the Asia‑Pacific region. Even in the “high‑growth” segment—small and mid‑size firms that are more agile in technology investment—the gap remains significant.

Why the Gap Exists

Talent Shortage. Canada’s financial‑tech talent pool is highly competitive, but many wealth‑management firms struggle to attract the data scientists and AI engineers required to build and maintain sophisticated models. An interview quoted in the article with Dr. Laura Cheng, a leading academic at the University of Toronto’s School of Economics, highlighted the mismatch: “We have great talent academically, but the industry is still in its infancy when it comes to AI. Firms often lack the incentive structure to develop or hire the right skill set.”

Legacy Systems. Many Canadian firms still rely on “big‑iron” platforms from the 1990s and 2000s that are not designed to ingest or process the large, heterogeneous data sets that modern AI models require. Updating or replacing these legacy systems is costly and fraught with regulatory compliance challenges. A senior technology officer at a leading Canadian advisory firm explained that “our core operations are built around COBOL‑based infrastructure; moving to a cloud‑native AI stack is a multi‑year project.”

Regulatory and Privacy Concerns. Canada’s privacy regime, governed by the Personal Information Protection and Electronic Documents Act (PIPEDA) and various provincial regulations, places a high burden on firms that wish to leverage customer data for AI training. In addition, the investment‑advisory sector is regulated by multiple provincial securities regulators, which adds another layer of complexity. The article links to a regulatory‑analysis piece (see “Regulatory Landscape” in the article) that provides an overview of how Canadian law differs from the U.S. Securities and Exchange Commission (SEC) approach.

Capital Allocation. Wealth‑management firms, especially those that are small or mid‑size, often have tighter budgets than global competitors. A note in the report indicates that only 9 % of Canadian firms report that AI projects have been fully funded within the past 12 months, compared to 25 % in the United States.

The Benefits That Are Being Missed

The study highlights several competitive advantages that AI can bring to wealth‑management firms:

1. Enhanced Investment Insight – AI models can sift through thousands of news articles, earnings transcripts, and macro‑economic data in real time, identifying patterns that would take human analysts weeks to surface. BlackRock’s Aladdin platform, for example, is cited as a benchmark for AI‑driven portfolio optimization.

2. Personalized Client Experience – Chatbots and recommendation engines can deliver tailored financial advice 24/7, freeing human advisers to focus on relationship‑building. Asian wealth‑management firms such as Nomura have reported a 20 % uptick in client satisfaction scores after deploying AI‑powered chat solutions.

3. Operational Efficiency – Automation of routine compliance checks and risk analytics can cut manual labor hours by 30–40 %, freeing resources for higher‑value tasks. In the U.K., firms using AI‑based compliance bots reported a 25 % reduction in audit cycle times.

4. New Revenue Streams – AI‑based robo‑advisory services allow firms to reach a broader customer base at a lower cost. The U.S. market has seen the rise of “high‑net‑worth robo‑advisors” that combine algorithmic portfolio management with personal advisory services, generating a new segment of fee‑based income.

How Canadian Firms Are Responding

The article profiles a few Canadian firms that are already making strides in AI adoption:

• CIBC Private Wealth has partnered with a fintech start‑up to pilot a natural‑language processing (NLP) tool that translates client requests into actionable data queries. The pilot reportedly increased portfolio optimization speed by 15 %.

• BMO Wealth Management is exploring machine‑learning models to predict client churn, aiming to intervene before clients leave for competitors.

• RBC Global Asset Management has begun building an internal data science team focused on developing AI tools for risk analytics, citing the need to meet the demands of “next‑generation” institutional investors.

Despite these initiatives, the article notes that most Canadian firms remain in the “early adopters” phase, with only a handful experimenting in a fully integrated manner.

The Bottom Line

Canada’s wealth‑management sector is at a pivotal moment. While the industry has historically been a global leader in fiduciary standards and client service, the rapid acceleration of AI in the global financial services arena means that firms that lag behind risk losing market share, client trust, and long‑term profitability. The study’s data underscore the urgency for Canadian wealth managers to:

1. Invest in Talent Development – Offer data‑science training to existing staff and create attractive career paths for external hires.

2. Modernize Technology Infrastructure – Move towards cloud‑native platforms that can easily interface with AI frameworks.

3. Align Regulatory Compliance with Innovation – Work with regulators to streamline data‑sharing rules and develop “sandbox” environments for safe AI experimentation.

4. Prioritize Client‑Centric AI Use Cases – Start with high‑impact, low‑complexity projects such as chatbots or automated portfolio rebalancing, then scale.

In the words of a senior analyst quoted in the article, “AI is not just a new tool—it’s a new paradigm that redefines how wealth managers create value. Canadian firms have the expertise to succeed; they simply need to act decisively.” The full study, available through the link embedded in the original article, offers a deeper dive into the methodology and provides actionable insights for firms that want to bridge the AI adoption gap.