A short course covering the basics, risks and realistic uses for a professional services firm.
Key takeaways
This lesson distinguishes between AI that drafts, AI that summarises, and AI that claims to reason independently through a legal or financial question. Nearly every credible use case in professional services falls into the first two.
Partners leave this lesson with a shared vocabulary that makes vendor conversations far more productive.
Client confidentiality obligations, whether under law society rules or ordinary professional conduct standards, apply fully to any AI vendor touching client information. This lesson covers what to check in a vendor agreement before any pilot begins.
It also flags jurisdiction-specific guidance that some Canadian regulators and law societies have started issuing on AI use.
Using real examples from accounting, legal and consulting practices, this lesson shows where firms consistently see the fastest returns, intake, first drafts, research summaries, and where results are more mixed.
It also covers common overreach: firms that try to automate final judgment calls tend to see the least success and the most partner pushback.
The final lessons walk through designing a review checkpoint appropriate to your firm's size and risk tolerance, and scoping a first pilot narrow enough to evaluate honestly within a quarter.
Participants leave with a one-page framework for bringing any AI proposal to partnership for a decision, rather than debating from first principles each time.
A 30-minute call is enough to tell you whether AI pays for itself here.
