Randy Johnston and Brian Tankersley sit down with Alexis Kingsbury, author of Accrual Intentions, to unpack what he learned from building a deliberately extreme experiment: an accountancy practice staffed by eleven AI agents with their own roles, personalities, and responsibilities. Kingsbury explains that the project began as part parody and part management-science experiment, but quickly became a practical test of delegation, workflow design, controls, and human judgment.
The Accounting Tech Lab is an ongoing series that explores the intersection of public accounting and technology.
View the video below:
The central lesson is not that AI is either brilliant or useless. It is that AI can perform impressively on difficult tasks and still make simple, checkable mistakes. Kingsbury argues that firms should separate probabilistic AI work from deterministic processes, document workflows, insert stage gates, and decide explicitly where human review belongs. He warns leaders not to confuse delegating the work with delegating the thinking.
The discussion also covers token economics, local models, model portability, and the risk of locking organizational knowledge inside one AI vendor’s project environment. Kingsbury recommends keeping core context, processes, and organizational knowledge in systems the firm controls, then connecting AI tools to that context.
His closing advice: do not wait for perfect AI, and do not attempt a giant transformation. Pick a painful, valuable problem, solve it deeply, learn, and expand.
.
Sign in to get access to this free resource, and all of our whitepapers and reports.
Download this content today!
Register Now Already registered? Click here to Log In