Last week, I wrote about how accounting helped make economic life visible and then gradually disappeared into the back office. Near the end, I made an observation that deserves more attention:
The stereotype survives because it contains an uncomfortable amount of truth.
Accounting has spent years trying to improve its image. But we will not change the profession’s reputation through better advertising. We will change it by redesigning the experience that produced the reputation in the first place.
I have spent more than 30 years at Wiss and in public accounting. During that time, I have watched extraordinarily capable people enter the profession with the promise that they would understand businesses, solve difficult problems and build trusted relationships.
That promise can come true. But historically, we have asked people to pay a substantial price before they are allowed to experience it. The cost is not only the hours. It is also the kind of work they have had to slog through for years: manual preparation, administrative tasks and recurring production that leaves little room for judgment.
The bargain was simple. First, prove that you can endure the work.
The Bargain We Made with Young Accountants
Each industry has a psychological contract with the people who enter it. The established norms make the exchange clear.
Accounting’s traditional contract has gone something like this:
Give us your early years. Work the long nights. Surrender parts of your weekends. Learn through repetition. Demonstrate that you can be relied upon when the pressure is highest. In return, we will give you technical mastery, professional credibility, economic security and, eventually, access to more meaningful work and perhaps partnership.
For many people, including me, that bargain worked. Public accounting provided an extraordinary foundation and an opportunity to understand businesses from the inside. It prepared people to become controllers, CFOs, CEOs, partners, bankers, entrepreneurs, consultants and advisers.
The difficulty was that the sacrifice arrived immediately and visibly, while the promised reward remained distant and uncertain.
Some people eventually reached the work they had imagined. Others concluded that the work they were doing was the profession and left before they ever experienced life as a trusted adviser.
We often interpreted that departure as a lack of commitment. Some of it may have been a rational response to the bargain we were offering.
The Early Years Were Not Worthless
The apprenticeship model itself was not the problem. In fact, the way many of us were trained was one of the most valuable reasons to begin a career in public accounting. There was real developmental value in doing the work.
Reconciling an account teaches you how transactions move through a business. Testing evidence teaches you to distinguish an assertion from support. Preparing a tax return teaches you how the tax code interacts with economic reality and where it differs from accounting standards. Working through a close teaches you where processes break, where estimates enter the numbers and where seemingly small mistakes compound.
Repetition creates pattern recognition and awareness. An experienced accountant sometimes sees that something is wrong before being able to explain precisely why. That instinct is not magic. It is often the product of encountering hundreds of variations of similar problems.
But repetition and development are not the same thing.
A person can perform a task 500 times and develop increasingly sophisticated judgment. When that person is asked to perform the same task 500 more times without greater context, feedback or responsibility, the remaining lesson may be only how to complete it faster.
Accounting has not always been honest about that distinction. We assumed that because the work had to be done, doing it must be developmental.
Sometimes it was. Sometimes it was just work.
When Endurance Became Part of Our Identity
Busy season began as an operating reality. Over time, it became part of accounting’s identity.
We shared stories about all-nighters and impossible deadlines with a strange mixture of horror and pride. Surviving them became evidence that someone belonged. Hours were easy to measure and reflected effort. Effort demonstrated commitment. Commitment became a proxy for potential.
Eventually, exhaustion itself began to look like excellence.
Think about the scene in Jaws where the men sit around the table comparing scars. Each scar proves what its owner has survived.
Public accounting has often worked the same way. Show me your busy-season scar tissue, and I will show you mine.
That created a hierarchy in which the people who endured the production system earned the right to move beyond it. Meaningful client interaction, interpretation and decision-making were treated as privileges that arrived after someone had accumulated enough technical experience and enough scar tissue.
But there is an obvious contradiction in that model. We recruit intelligent and curious people because of their potential to exercise judgment. Then we consume most of their attention proving they can execute.
We built an apprenticeship model for an era in which labor was the production system. We told people they would become advisers, but advisory was something they were expected to learn after the deadline, after the engagement and after the work we already measured had been completed.
AI Breaks the Old Bargain
Artificial intelligence is beginning to perform portions of the work on which accounting built its apprenticeship model.
Agents can collect documents, extract information, categorize transactions, prepare reconciliations, assemble workpapers, identify exceptions and produce initial explanations.
The immediate debate has focused on jobs. What happens to entry-level accountants if machines perform entry-level work?
That is an important question, but a more consequential one comes first:
What experiences will develop judgment when repetitive production is no longer the primary training ground?
If we remove the bottom rungs of the ladder, we cannot tell people to climb harder and faster. We need to build a new ladder.
AI does not eliminate accounting’s apprenticeship problem. It exposes how heavily our apprenticeship model depended on production rather than intentional development.
We inherited a production system and called it development. Now that the production system is changing, we can become much more deliberate about how development actually happens.
What Should Replace the Old Work
The answer is not to fast-forward people into high-stakes judgment. Technical foundations and professional skepticism still matter.
The goal is not to eliminate rigor. It is to stop confusing rigor with suffering.
The new apprenticeship should move people into the context surrounding the work much earlier. Young accountants should:
· Participate in client conversations earlier, first as observers and then as contributors.
· Move from merely identifying exceptions to investigating and explaining them.
· Compare AI-generated conclusions with the underlying evidence.
· Explain why a system’s proposed answer should be accepted or corrected.
· Learn how accounting policies affect operating decisions.
· Practice presenting financial results to people who are not accountants.
· Observe experienced professionals making consequential judgment calls and discuss how they reached them.
Judgment is not developed through observation alone. But it is very difficult to develop when young professionals are excluded from the rooms where judgement is exercised and formed.
What We Are Confronting at Wiss
We are beginning to confront this at Wiss through our work with Basis. In selected workflows, Basis prepares portions of recurring accounting work while our professionals review the support, investigate exceptions and determine whether the conclusion can be defended.
The technology changes more than the time required. It changes what we ask people at each level to do.
If Basis completes more of the recurring preparation, we have at least two choices.
We can use the capacity to complete more of the same work. The economics are easy to calculate. If an accountant gets several hours back, we can add more clients, more returns or more engagements. That may be a perfectly rational use of some of the capacity.
But if every hour returned by AI flows immediately back into production, we will have made the old operating model faster without making the profession better.
The other choice is to reinvest some of that time in what the old model struggled to produce: client exposure, business context, exception investigation, industry knowledge, communication and the ability to turn trusted information into action.
Whether firms use the capacity for development or merely fill it with additional volume will be a leadership choice.
The greatest return from AI may not be the additional work an accountant can complete. It may be the accountant that person can become.
The Measurement Problem
This transition will be difficult because the old system reinforces itself. As the saying goes, what gets measured gets managed.
If we tell people to use AI but continue measuring them primarily through hours, utilization and units of production, the system will pull them back toward the work it already knows how to value. Efficiency that creates unused time can feel dangerous in an organization that values visible busyness.
Most of us recognize the problem. The person who completes work quickly is rewarded with more work. A manager wants to reduce hours for the health of the team but worries about the effect on revenue. A partner may support innovation while remaining accountable for traditional production economics.
None of this makes people resistant to change. It makes them responsive to the system around them.
If firms want different behavior, they will have to measure different things:
How much administrative and preparation effort was eliminated?
How many exceptions did AI identify before a person began reviewing?
How much time did professionals spend with clients?
How quickly did someone progress from preparing information to explaining it?
Did the capacity created by AI improve the client’s decisions, the employee’s development or simply the firm’s volume?
The profession’s actual priorities will not be revealed by what it says about AI. They will be revealed by where the saved hours go.
A New Psychological Contract
Accounting needs a new bargain. What if the unwritten contract inside our firms sounded more like this?
We will still expect rigor, responsibility and hard work. We will still expect you to master the technical foundation of the profession. But we will not make exhaustion the price you pay for meaningful work.
We will expose you to clients, judgment and business context earlier. We will teach you how to work with intelligent systems without surrendering professional skepticism. We will measure your development not only by how much work you complete, but by the quality of the questions you ask, the conclusions you can defend and the value you help create.
In return, we will expect you to remain curious, accept accountability and develop the distinctly human capabilities that become more, not less, important as machines perform more execution.
That would be a better bargain for our people and, ultimately, for our clients.
What Accountants Are Asked to Become
The accounting talent shortage is usually discussed as a supply problem. There are many explanations for why fewer people have chosen the profession.
But we should also acknowledge that supply reflects the product we offer people.
If the experience remains punishing, the progression remains slow and the most meaningful work remains postponed, promises alone will not repair the pipeline. The profession cannot advertise its way out of an experience it is unwilling to redesign.
AI gives us the opportunity to do more than remove tasks. It allows us to reconsider the relationship between production and development, between hours and value, and between technical competence and business judgment.
We should not waste that opportunity by using intelligent systems only to increase throughput.
If accounting once mistook exhaustion for excellence, AI gives us the opportunity and the obligation to finally separate the two.
A Note on What Comes Next
At Wiss, we are working with Basis to test this different operating model: AI agents performing more recurring accounting preparation while professionals retain responsibility for review, judgment and interpretation.
Over the next several installments, I will share what we are learning, including where the model works, where it struggles and what must change inside a firm for AI to create something more valuable than additional capacity.
If your finance team is struggling with a close built around spreadsheets, manual preparation and recurring heroics, please feel free to reach out to me at ppeterson@wiss.com. I’m happy to provide you with any help I can provide.
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