Everywhere I turn, someone is talking about Artificial Intelligence. Software companies are racing to release new features, business owners are experimenting with tools they discovered last week, and accounting professionals are trying to determine what all of this means for the future of our profession. Depending on who you ask, AI is either going to revolutionize everything we do or replace us entirely. As someone who has spent decades working with business owners, financial information, audits, and advisory services, I find myself having a very different conversation.
I don’t believe the real question is whether AI will replace accountants and bookkeepers. In fact, I think that question misses the point entirely. The real question is whether we will continue to apply the human judgment, critical thinking, and practical experience that businesses have always needed. Technology changes. It always has. The spreadsheets replaced the ledgers. Cloud software replaced desktop software. Automation reduced manual processes. Each change altered how we worked, but it didn’t eliminate the need for professionals who could interpret information, apply judgment, and help business owners make sound decisions. AI is simply the next evolution in that journey.
I use AI regularly in my own businesses. I am not afraid of it, and I certainly don’t believe professionals should ignore it. Quite the opposite. I believe accounting professionals need to embrace it, learn it, test it, and understand it better than many of the clients they serve. The reality is that our clients are already using it. They’re asking ChatGPT tax questions. They’re using AI to draft business plans. They’re generating budgets, researching deductions, and looking for answers online before they ever pick up the phone and call us. Pretending AI isn’t happening won’t protect our profession. Understanding it will.
What concerns me most isn’t the technology itself. It’s how quickly people are willing to trust it. Throughout my career, one of the most important lessons I’ve learned is that numbers don’t exist in isolation. Every number tells a story. Every financial statement reflects decisions, assumptions, and circumstances that require context to understand properly. Yet when AI enters the conversation, I often see people abandon the healthy skepticism they’ve spent years developing. Because a machine produced an answer, they assume it must be correct. Because software categorized a transaction, they assume it was categorized properly. Because a report looks professional, they assume the underlying information is accurate.
In my opinion, that’s where the real risk lies. Not in AI itself, but in our willingness to lower our guard simply because technology produced the answer. I’ve often described this as automation bias with a human signature. The software provides a result, the user glances at it, assumes it’s right, and clicks approve. That isn’t oversight. That’s trust without verification. As professionals, we’ve spent years teaching business owners not to blindly trust their numbers. We shouldn’t start blindly trusting the technology producing those numbers.
The truth is that AI still makes assumptions. It fills in gaps. It predicts what it believes is most likely based on the information available to it. That’s not a criticism of AI. It’s simply how the technology works. The challenge is that business decisions, tax decisions, and financial decisions often require more than probabilities. They require context. They require understanding. They require judgment. A tax authority doesn’t review a transaction and ask whether software categorized it correctly. They ask why it was categorized that way in the first place. They want supporting documentation. They want rationale. They want evidence. AI may be able to organize information, but it cannot defend a decision. That responsibility still belongs to professionals and business owners.
This becomes especially clear when I work with clients on profitability and cashflow planning. One of the most common situations I encounter has nothing to do with AI and everything to do with context. A business owner proudly shows me their financial statements and explains that they’re making money because the profit and loss statement says they are. On the surface, the numbers look healthy. Revenue is strong. Expenses seem reasonable. Profit exists on paper. But then we begin asking questions. How many hours are they working? What would it cost to replace them tomorrow? Are they paying themselves appropriately for the work they’re performing, or are they effectively working for free?
The answers are often eye-opening. Many business owners have unknowingly created a situation where they are subsidizing the business with their own labour. They’re working evenings, weekends, and holidays. They’re handling tasks that would normally require employees. They’re absorbing costs that aren’t reflected anywhere in the financial statements. The result is a business that appears profitable until we account for the true cost of operating it. That’s usually when I deliver a difficult message: you’ve built a very expensive hobby. The numbers weren’t wrong. They were incomplete. Without context, even accurate information can lead to poor decisions.
That lesson applies directly to the AI conversation. Business owners don’t need more data. Most already have access to more information than they know what to do with. What they need is someone who can help them understand what that information means. They need someone who can challenge assumptions, identify blind spots, and ask the questions that software cannot. In my experience, the most valuable conversations rarely begin with a report. They begin with curiosity. Why is this happening? What changed? What aren’t we seeing? What assumptions are we making that may no longer be true? Those conversations create better decisions, and better decisions create stronger businesses.
When people ask how I use AI, I often tell them I treat it like the most junior employee on my team. That’s not meant as an insult. Junior employees can be incredibly valuable. They can save time, perform research, gather information, and support larger projects. But no experienced professional would take a junior employee’s work, glance at it for two seconds, and immediately send it to a client. We review it. We ask questions. We verify the work. We provide coaching and oversight. AI deserves the same treatment. In many ways, it knows the theory remarkably well. What it lacks is the practical experience that comes from years of applying that theory in the real world.
Anyone who has spent time in a profession understands the difference between theory and practical application. A textbook can explain the rules. Experience teaches you when those rules apply, when they don’t, and what exceptions you need to consider. Over time, professionals develop pattern recognition that can’t easily be taught. We can glance at financial statements and sense that something feels off. Maybe the margins look unusual. Maybe payroll seems low. Maybe an expense account doesn’t align with what we know about the business. We don’t always know the answer immediately, but we know where to look. We know which questions to ask. We know when something deserves a second look. That’s not information. That’s judgment.
Ironically, the more advanced AI becomes, the more valuable certain human skills become. Communication becomes more valuable. Relationships become more valuable. Critical thinking becomes more valuable. Advisory services become more valuable. The future of our profession isn’t going to be defined by who can process transactions the fastest. Technology will continue to improve that process. The future belongs to professionals who can translate information into insight and insight into action. It belongs to professionals who understand the goals behind the numbers and who can help business owners navigate uncertainty with confidence.
If I have one concern about the future, it isn’t that AI will become smarter. It will. My concern is that people may stop exercising the critical thinking skills that made them valuable in the first place. The temptation to accept answers without questioning them is real. The temptation to let software do the thinking for us is real. Yet the responsibility remains exactly where it has always been. Business owners are still responsible for their businesses. Professionals are still responsible for their advice. Technology may assist us, but it does not assume accountability for the decisions we make.
For business owners, I believe there is a simple question worth asking every advisor, accountant, or bookkeeper you work with. Don’t ask whether they use AI. Most already do, and many should. Ask them how they use it. Ask what safeguards they have in place. Ask how client information is protected. Ask how recommendations are reviewed before they reach your desk. Ask how professional judgment is applied. The answers will tell you far more about the quality of advice you’re receiving than the technology itself ever could.
AI will continue to evolve, and I welcome that evolution. It will help us work faster, analyze information more efficiently, and eliminate many repetitive tasks that consume valuable time. What it won’t do is replace the need for human judgment, human context, and human intelligence. Those qualities have always been at the heart of good advice, and they will remain there long after today’s technology becomes tomorrow’s history.
AI can process the numbers. It still can’t understand your business.
Read more on thought leadership at The AI Agreement Illusion: What Women Leaders Build Before AI Meets Reality
