AI Is Killing the Way Accountants Learn. Here's What's Replacing It.

AI is taking over the grunt work young accountants used to do to learn the job. That creates a problem: How do you train people when the training work is disappearing?

The Journal of Accountancy's March issue digs into this question, and the answer isn't "just let AI do it." It's about teaching people to supervise AI instead of executing tasks themselves.

The Old Training Model Is Dead

Carl Mayes, vice president of CPA Candidate Quality & Competency at the AICPA, started his career 20 years ago by vouching — comparing transactions in accounting records to invoices and receipts to make sure everything matched.

Today? AI does that automatically.

"Commercially available AI-powered platforms for audit and advisory firms have vouching tools that will do that for you and that is going to save so much time," Mayes said.

That's great for efficiency. But it creates a training problem. Young accountants used to learn about systems, controls, and professional skepticism by doing repetitive work. Now that work is automated. So how do they learn?

From "Doing" to "Supervising"

The profession's answer: teach people to supervise bots instead of doing the work themselves.

"When it's a bot doing it, you need somebody to supervise that bot," Mayes said. "We can't just accept that the bot has done it right. For us to supervise the bot, we have to understand the underlying procedure, even if we're never going to do the procedure ourselves."

That's a fundamental shift. You don't need to know how to vouch 500 transactions manually. But you need to know what vouching is, why it matters, and how to tell if the AI screwed it up.

This means training has to pivot from memorization to conceptual mastery. Teach the principles. Teach the "why." Teach how to evaluate outputs critically.

AI Affects All Levels, Not Just Entry-Level

David Wood, a professor at BYU, said AI's impact isn't just hitting staff-level work — it's affecting seniors, managers, and partners too.

He built an Excel tool that automated parts of the review process. Reviewing is normally a senior, manager, or partner job. But his tool lets entry-level staff catch problems before sending work to their manager.

"They get detailed feedback and improve without requiring training time from their manager," Wood said. That compresses learning cycles — people learn faster because AI gives them instant feedback.

Use AI as a Training Partner

Wood also came up with an approach where students teach AI as part of their training.

"Students don't remember a lot from sitting and listening to a lecture," he said. "But if they teach somebody else, they remember a ton. So we thought, what if we had them mentor an AI?"

Instead of reading and testing, students train a deliberately "ignorant" AI until it can pass an exam. The approach flips learning from passive to active and mirrors how modern professionals will actually work with AI.

They're also using AI personas to practice interviewing. "They get practice and feedback on both their [people] skills and interviewing skills," Wood said.

Theoretical Understanding Isn't Enough

Elizabeth Mason, CEO of High Rock Accounting, said there's a growing gap between the theoretical knowledge graduates have and the application skills firms need.

"A student will graduate understanding how to do lease accounting from a theoretical perspective," she said. "But you ask that student to apply that, saying, 'Go ahead and book these 10 leases,' and they have no idea how to create the right spreadsheet."

Her solution? Build AI into firm training. Create a RAG (retrieval-augmented generation) system trained on the firm's own datasets — reconciliations, processes, workflows — so new hires can ask it anything and get firm-specific answers.

The risk? They might not be able to review the output. "It's really about putting in controls at the firm level around a review of work," Mason said.

What Future Training Looks Like

The experts agreed on a few key shifts:

• Conceptual understanding over mechanical execution: Accountants must understand why processes exist, not just how to perform them.

• Supervision of AI: Train people to evaluate, challenge, and govern automated work.

• Simulation-based learning: 3D environments, AI role-play, and scenario training replace passive lectures. (Wood built a 3D simulation where students audit inventory in a virtual warehouse.)

• Cross-level training: Interns and partners must learn together, not separately.

• Human skills as core curriculum: Communication, consulting, judgment, and trust building will define professional value when AI handles the technical work.

• Continuous upskilling: There's no stable endpoint, only lifelong learning.

What This Means

The AICPA just launched "Profession Ready," an initiative focused on early-career skills gaps and "where the puck is going versus where it is today." Findings are expected in 2027.

In the meantime, firms and universities are figuring this out together. Wood put it well: "This is a unique time in history where everybody starts the race at the same level."

AI isn't replacing accountants. It's replacing the way accountants are trained. And the profession's scrambling to figure out what comes next.