Real AI workflows, compliance risks, and client trust on the agenda in Toronto this September
Artificial intelligence has moved from conference buzzword to daily business reality for a growing number of Canadian mortgage professionals.
Whether brokers are automating client follow-ups or using AI to accelerate file preparation, the question is no longer whether to adopt the technology — it is how to do so without losing efficiency, accuracy, or client trust.
That tension sits at the heart of one of the headline sessions at the 2026 Women in Mortgage Summit Canada (WIMS), which takes place on September 24, at the International Centre in Toronto.
The workshop panel — titled "AI, In Practice: Real Mortgage Workflows, Honest Results" — is designed to cut through the noise surrounding artificial intelligence and deliver practical, field-tested guidance to mortgage brokers and lending professionals across Canada.
No vendor pitches, no theoretical frameworks: just documented workflows from practitioners actively managing files today.
At the #WomenInMortgageCA Summit 2026, you'll join 600+ industry professionals for a day dedicated to tackling today's biggest challenges and preparing for tomorrow's opportunities.
— Canadian Mortgage Professional Magazine (@CMPmagazine) June 30, 2026
Register today and be part of the conversation!
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What the session will cover
Three speakers with distinct vantage points across the mortgage industry will share how they have integrated AI into their day-to-day operations, and where they have hit limits.
Dalia Barsoum, founder of Streetwise Mortgages in Ontario, brings a broker's perspective built on years of working with investor clients and complex portfolios.
Tracey Robinson, principal of relationship management and strategic development at Filogix, approaches AI from the technology and lender-relationship side of the industry.
Lisa Evans, director of underwriting at Magenta Capital Corporation, will address how AI intersects with the credit and risk functions that underwriters manage daily.
Together, the panel will examine which tasks are already being handed off to AI — among them client communication, file preparation, follow-up sequencing, and marketing — and how professionals are doing it without surrendering their professional voice.
The session will also address where cutting corners with AI creates more work, or more risk, than it saves. Compliance obligations, data privacy considerations, and the mechanics of maintaining client trust will be covered directly.
The format promises step-by-step workflows that teams can implement, rather than high-level concepts that require translation before they become actionable.
A broader day for Canada's mortgage women
The AI session is one of several practical, professionally focused conversations on the WIMS agenda.
Mortgage brokers attending the full day of programming at the International Centre will also hear from Sherry Cooper, chief economist at Dominion Lending Centres in Toronto, on navigating market uncertainty, buyer hesitation, and the strategic opportunities embedded in a slower environment.
A separate panel on leadership sustainability will address the burnout risks that come with high performance, exploring how to delegate effectively, set boundaries, and build careers that are not just successful but sustainable over the long term.
The event is chaired by Leah Zlatkin, chief operating officer of Mortgage Outlet Inc. in Toronto, who has been a recurring voice in Canadian mortgage coverage on market trends and broker strategy.
Registration for WIMS 2026 also includes full access to MortgageFest Canada on both September 23 and 24. The combined programme spans market economics, prime lending, compliance, and the mortgage renewal wave currently reshaping client books across the country.
Why the AI conversation matters now
The timing of the session reflects a broader shift in the Canadian mortgage industry. Brokers who have spent years building relationships on the strength of personal service are now being asked to evaluate which parts of that service can and should be delegated to machine learning tools, and which parts remain irreducibly human.
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