Putting Your Name on AI Work: Professional Accountability for Work Created with AI assistance

An AI-drafted tax memo cites authorities nobody has checked. A junior pastes a client’s T2 working papers into a personal ChatGPT account. A draft invoice says ten hours when about four were worked. On the same Monday, a client wants a return filed based on a ChatGPT answer. Nadia Rahman, a fictional manager at an Ontario accounting firm, has to decide what happens next. 

While the course is aimed at CPAs, its practical lessons are transferable to legal practice, with value for both lawyers handling client work and managing partners setting firm policy. 

Through twelve decision points, Dr. Jason Dean asks viewers to work through a fabricated citation in a delivered report, a memo due before anyone has read its authorities, a data leak a partner wants kept from the client and a fixed-fee client who asks whether AI should reduce the price. A second running case follows Omar Haddad, a controller using AI in a company’s finance work. 

The course explores how much checking an AI output needs, how to test a tool’s reliability and how to avoid both undue trust in AI and the dismissal of a correct warning. It also examines what may be entered into personal and business AI accounts, Canadian privacy and breach considerations, supervision, billing and communication with clients.

Participants receive a one-page AI policy template, a vendor checklist, illustrative engagement-letter wording and five incident-response steps.