Will AI Replace Accountants?
Updated: Sep 7
A CPA’s perspective on artificial intelligence, professional judgment, client trust, and the future of accounting.
I recorded a 25-minute conversation about artificial intelligence and accounting while sitting in the carpool line because this topic keeps coming up across the profession.
AI has become one of the most discussed topics in accounting. It shows up as a breakout session at conferences, a webinar topic, a CPE course, and a discussion among practitioners comparing what AI looks like inside their firms and companies. Accounting students and new professionals are asking the same question from a different place: they wanna know what their careers will look like now that AI is in the mix.
AI will not replace accountants.
AI will absolutely change the work. Some tasks will disappear. Some roles will shrink. Accountants who refuse to learn the technology may find themselves standing still while the profession moves around them. None of that means the profession is going away.
AI can produce an answer. Accountants still have to know whether that answer makes sense, explain what it means, and take responsibility for what happens next.
Accounting Beyond Debits, Credits, and Journal Entries
Sometimes the conversation about AI and accounting gets too small because people reduce accounting to transactional work. They think about debits and credits, journal entries, reconciliations, accounts payable, and accounts receivable. Those functions are important, but they represent a fraction of what the accountants actually do.
Accounting is a hub and spoke thing: Accounting is the hub (center) and the spokes are the different pathways (audit, general ledger, tax, internal controls, financial reporting, systems, etc.) that we can choose, get settled in, and pivot out of. We create standard operating procedures and job aids. We help companies understand the technology they already own. We investigate variances, build business cases, evaluate risks, explain results, and help leaders make decisions.
Most accountants also have internal customers. These are the department leaders, executives, P&L owners, and operational teams throughout a company that depend on our expertise, judgement, and recommendations. They come because they need the business story of what happened.
Imagine that the supply chain team wants to purchase new software to track orders moving through the sales order process. These conversations often start with, “I’m not an accountant but…
They wanna know how the purchase fits into next year’s budget. They need help calculating the return on the investment. They may need a business case that can survive executive review and get the purchase approved. Procurement, technology, legal, finance, and operations may all touch the decision.
AI won’t replace accountants. It will force us to become better accountants.
AI can help organize this information from the data sources and produce a business case or ROI calculation. The accountant still knows how the company budgets, who approves the spending, how similar purchases were treated, which controls apply, and where the financial impact will land.
That company context rarely fits inside one AI prompt.
The same thing happens when a P&L owner sees an extra $42,318.71 or $80,000 sitting in an expense line and asks, “What happened this month?”
An AI-generated paragraph could potentially describe the variance, if you choose to upload confidential financial data into an AI tool that’s (1) public and (2) can make mistakes. They need someone to investigate the transactions, determine whether the activity belongs there, explain what changed, decide whether something needs to be corrected, and still do the correction.
The best accounting teams provide that information before the department owner has to ask because they understand that person is one of their customers.
Every AI Tool Tells Us the Part We Keep Minimizing
Nearly every AI tool I’ve used includes some version of the same warning: the tool can make mistakes, so you need to verify the information.
We need to stop treating that disclaimer like tiny footer language nobody reads.
Verification is the foundation of accounting as we don’t play in gray areas. We reconcile balances, trace transactions, evaluate support, test evidence, investigate differences, and question whether the numbers tell a complete story. A clean answer can still be the wrong answer and a polished explanation can still rest on a bad assumption.
AI tools also hallucinate. They can combine unrelated information, misunderstand a request, invent a source, or present the wrong conclusion in a tone that sounds remarkably sure of itself.
People make mistakes too. I would still rather deal with a mistake made by a trained human who understands the business, can investigate what happened, explain the reasoning, correct the work, and remain accountable for the conclusion.
The disclaimer at the bottom of an AI tool cannot sign a tax return or explain an audit judgment to a partner or defend a control conclusion. It cannot sit across from a chief financial officer and answer the rapid-fire questions from the live P&L review which can change the entire analysis.
Accountants still have to own the answer.
Will AI Replace Accountants? AI Needs An Accountant
Let’s separate supplemental AI from generative AI.
Supplemental AI helps a knowledgeable person develop, test, organize, or communicate work. It can help you research a topic, find information, draft a process document, identify patterns in data, or strengthen an analysis you’ve already performed.
Generative AI becomes a problem when people expect it to be the brain.
Tell an AI tool to create a financial statement, and it can create something that looks like one. Then the questions begin:
· What type of company is this?
· Which accounting framework applies?
· What period are we reporting?
· Do you want a single step or multistep income statement?
· Who will use the financial statement?
· What decision are they trying to make?
· Has the underlying activity been reconciled?
· Are the classifications correct?
You still have to give the technology good information. You also need enough accounting knowledge to evaluate what comes back.
That’s the part people skip when they say AI can do the work. Producing an output and completing the work are two different things.
The output you get from your laptop will mimic the AI-generated financial statements your peers from across the city, in another state, and even on another continent also generated. You and your peers have different numbers, companies, accounting periods, industries, objectives, and questions to answer, yet you all accept the same output with those oversized headings, ugly fonts, unnecessary emojis, and questionable calculations that you assume to be the gospel. This is where AI becomes dangerous for accountants.
The depth and quality of the information you provide will shape the result. The experience of your customers \will determine whether your work product gets you praised or dragged.
Generic Prompts Are Already Exposing Generic Thinking
I realized how widespread this “defaulting to AI” problem had become while scrolling social media. I saw the same message posted by different accounts on different platforms. At first, I thought it might be one person using different usernames.
Then it happened again on different days with different accounts posting the same captions.
These people were probably asking an AI tool to “create a motivational post” or “write social media content about wellness,” then publishing the first output AI generated. They gave the technology inputs that were nothing distinctive, so it returned outputs that nothing distinctive.
You can read some content and immediately know AI did it. The same common words and sentence structure shows up. Everybody suddenly wants to tell you something “isn’t just” one thing, that it’s “more than” another thing, that something “matters” and that the answer involves some combination of confidence, purpose, and a journey nobody remembers taking.
The work begins to sound like nobody because everybody is publishing the same thing.
That same behavior is dangerous in accounting. A generic request can produce a polished response that ignores the facts capable of changing the conclusion. Accountants cannot accept the initial AI output just because the formatting looks professional and the wording sounds complete.
We have to question the assumptions, add the missing business context, and verify the result. You cannot properly review work you don’t understand. And why expend energy to feed all this information to AI when you can use your brain to achieve a better outcome?
As a millennial, I have to acknowledge that AI meant Allen Iverson long before it meant artificial intelligence to me. The one and only. Now that we’re using those letters for technology, we should spend more time thinking about the word “artificial.” The tool can generate, but it doesn’t have lived experience. It doesn’t know your company because it attended the meetings, watched the decisions unfold, or dealt with the consequences.
It knows what you give it and it creates overused filler content for what you don’t give it.
Client Confidentiality Is Where My Curiosity Stops
As a CPA and firm owner, I have a hard boundary around client information.
My firm works with founders, private companies, family offices, high net worth individuals, small business owners, and athletes ranging from high school freshmen to collegiate and professional players. People are curious about some of the clients we serve, especially within name, image, and likeness. That makes protecting their identities and financial information even more important.
I’m unwilling to place client financial statements, tax data, identifying information, or confidential business details into a public AI tool. I’m also uncomfortable connecting my tax application, email, or other client systems to AI simply because an integration is available.
Convenience doesn’t outrank the trust clients place in me as a practitioner. I appreciate what the technology can help us do. Every firm needs to make informed decisions based on its systems, vendor agreements, security requirements, professional obligations, and risk profile. At a minimum, firms should establish written rules governing us of approved AI tools, permitted uses, confidential information, review requirements, and human responsibility.
The bigger question is whether the AI integration works. What data does the tool receive? Where does that information go? How is it retained? Who can access it? Can it be used to train the system? What happens when the output is wrong?
Accounting Students Still Need to Learn the Accounting
Accounting students should absolutely learn how to use AI. They should play around with different tools, understand it, and learn where it can compliment their work.
They also need to learn the accounting.
My concern reaches beyond the accounting profession. Children are growing up during a time when artificial intelligence can give them all their homework answers, and educators can use the same tools to build every lesson.
If we allow technology to replace the incubation of critical thinking, we’ll end up with a population of people who are content with the convenience of receiving subpar answers to life-changing situations without ever knowing whether it is right.
Future accountants still need to understand debits and credits, financial reporting, audit evidence, tax law, internal controls, systems, and business operations. They need to recognize missing information, question results that don’t make sense, communicate with stakeholders, and explain why a conclusion is THE conclusion.
The person who understands the cerebral work will know when the technology has taken a wrong turn, while the person without that foundation may follow it straight off the road.
According to the U.S. Bureau of Labor Statistics, employment for accountants and auditors is projected to grow five percent through 2034, with approximately 124,200 open jobs each year. The same agency projects a decline for bookkeeping and auditing clerk roles.
The World Economic Forum’s Future of Jobs Report 2025 presents a more cautious global forecast and identifies accountants and auditors among roles employers expect to decline.
The pressure of AI in accounting is undoubtedly building. Transactional work will continue to change, forcing the evolution of what an “entry level role” will look like going forward. Firms will need better ways to give new accountants the reps that help them develop the judgment, critical thinking, and storytelling skills that are essential to the accounting profession as we protect the public interest.
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