The Canadian legal profession has entered a more demanding phase of AI adoption.

• In the second quarter of 2026, 19.2% of Canadian businesses reported using AI to produce goods or deliver services, more than triple the 6.1% recorded two years earlier.
• Among businesses in professional, scientific, and technical services, the figure reached 32.4%.
• Thomson Reuters’ latest professional-services research shows a similar acceleration across the legal market: 41% of law firms and 47% of corporate legal departments now say their teams are using generative AI, up from 28% and 23%, respectively, in 2025.

The adoption question is no longer hypothetical.

Launching another pilot is no longer the hard part. The harder challenge is converting uneven experimentation into a governed, repeatable operating capability: workflows that lawyers actually use, controls that clients can trust, economics that leaders can measure, and knowledge foundations that make AI outputs more reliable.

That challenge sits at the center of Legal AI Toronto

The program brings together law firm leaders, in-house counsel, legal operations professionals, innovation and knowledge leaders, practicing lawyers, and technology executives to examine what it takes to move from isolated use cases to enterprise-wide impact.

The operating gap behind the adoption curve

AI may already be entering legal organizations faster than their operating models can absorb it.

Statistics Canada found that the proportion of Canadian workers using generative AI nearly doubled between September 2024 and July 2025, increasing from 17% to 30%.

The agency noted that the gap between worker and organizational adoption may indicate that some use is employee-driven, occurring alongside, or independently of, formal enterprise strategies.

Thomson Reuters has also found that one-third of lawyers, accountants, and compliance professionals are using unsanctioned AI, creating activity that their organizations may be unable to monitor or govern.

This is not simply a technology gap.

It is a management gap between individual behavior and institutional controls; between available features and redesigned workflows; and between promised efficiency and demonstrated business value.

Legal AI Toronto is built around closing that gap.

A program built around the real implementation questions

The day opens by examining the implications of Canada’s new AI for All strategy for the legal profession, including the expected growth in demand for advice on governance, privacy, intellectual property, compliance, and AI accountability.

From there, the agenda turns to the internal challenge of adoption. Sessions will explore how firms can increase meaningful AI use among lawyers and professional staff, manage technology fatigue, redesign work, and measure whether significant investment is translating into sustainable improvements in productivity and profitability.

Education is another central thread. As AI becomes embedded in research, drafting, review, and client delivery, firms must decide what technological competence now means for partners, supervising lawyers, junior associates, students, and business professionals. The program asks how firms can build AI curricula without weakening the foundational legal skills on which reliable judgment depends.

The client conversation follows. How is AI is allowing firms to deliver core work more efficiently while also making entirely new services viable, from portfolio-wide contract analysis to large-scale review and more strategic use of client data?

Governance receives dedicated attention through a discussion of privilege, confidentiality, access controls, information security, data ownership, and stakeholder accountability. The emphasis is not on slowing adoption, but on creating the practical guardrails required to accelerate it safely.

The afternoon moves from AI adoption to AI advantage: how firms can retain strategic control, connect AI investments to firm objectives, preserve institutional knowledge, and evaluate an increasingly crowded technology ecosystem through clearer governance models and performance indicators.

The day concludes with an executive discussion about what firms should prioritize over the next three to nine months, and what they should be preparing for over the next three to five years, as AI reshapes talent, investment, service delivery, pricing, and competitive positioning.

The through-line is clear: AI must move out of the innovation sandbox and into firm strategy, matter delivery, professional development, risk management, and the client relationship.

A cross-functional Canadian faculty

The announced faculty reflects the breadth of that challenge.

Among the confirmed speakers are Al Hounsell, Naïm Antaki, Michelle Fernando, Julie Wilson, Tania Djerrahian, Carmen Bruni, Simon Wormwell, Sarah Chan, Victor Dudas, Jessica Rubin, Laura Levine, Su Hutchinson, Laurie Hause, Eugene A. G. Cipparone, David Marshall, Sienna Molu, and Joe Marando, with additional speakers to be announced.

The diversity of the faculty reflects the reality that enterprise AI is no longer an innovation-team initiative. It touches practicing lawyers, partners, knowledge management, operations, technology, finance, risk, talent, and client-facing teams. Any successful adoption strategy must connect those functions rather than leaving each to develop its own approach.

Why this matters

Legal AI Toronto arrives shortly after the launch of Canada’s AI for All strategy, which targets an increase in national AI adoption from just over 12% to 60% by 2034. The federal government says the strategy is intended to generate an additional CAD 200 billion in economic growth and create 250,000 AI-related jobs over the next five years.

The national direction is clear: adoption is expected to accelerate.

At the professional level, however, the responsibilities surrounding that adoption are becoming more concrete. The Law Society of Ontario frames generative AI use through six existing obligations: competence, confidentiality, honesty and candour, supervision, reasonable fees and disbursements, and the duty not to mislead a tribunal. In November 2025, the Ontario Superior Court of Justice also introduced practice directions intended to promote transparency, accuracy, and accountability in the use of AI in civil and family proceedings.

Clients are adding another layer of pressure.

Thomson Reuters reports that 54% of corporate legal respondents believe their outside firms should use AI, yet fewer than 20% are formally requiring its use through guidelines or requests for proposals. At the same time, 40% of law firm professionals say they receive conflicting instructions from different clients. Just 18% of surveyed organizations currently collect metrics around AI return on investment.

Firms are therefore being asked to adopt AI while navigating unclear client expectations, emerging professional standards, evolving technology, and limited agreement on how value should be measured.

Against that backdrop, the event’s focus on governance, education, economics, knowledge, and client trust feels less like a collection of conference themes and more like an operating mandate.

The next competitive divide will not be between firms that have purchased AI and those that have not.

It will be between organizations that can demonstrate how AI is governed, embedded, measured, and translated into client value, and those still relying on scattered pilots and individual enthusiasm.

The pilots are running. Toronto will ask what it takes to make them count.

The Details

Legal AI Toronto takes place on Tuesday, October 27, 2026, in Toronto, Canada.

Registrations confirmed by July 31, 2026, receive a CAD 400 saving with the code AITORONTO.

Further information and registration are available through the Legal AI Toronto event page.