In this career‑advice video, CPA Bill Hanna answers a viewer’s question about whether accounting is a good career in 2026. He walks through a recent staff‑accountant hire, outlining which daily responsibilities have stayed the same despite AI (bank and credit‑card reconciliations, cash‑transaction posting, invoice and general‑ledger review, flux analysis, and financial‑close checklists) and which have been transformed by AI (automated categorization, AI‑generated invoices, AI agents that fill gaps in ERP functionality, document‑filling bots, AI‑assisted bank‑reconciliation discrepancy detection, and Excel formula generation). Hanna announces a new simulated ERP training product called Ledger Lab, slated for beta release in August 2026, which lets learners act as staff accountants in a virtual environment. He emphasizes that, even with AI, human judgment remains essential for reviewing AI outputs and making business decisions, and that the accountant’s role is shifting from pure number‑crunching to advisory work. He concludes that accounting remains a stable, evolving career path, especially for those willing to embrace AI‑augmented advisory responsibilities.
This video is a career advice for those who are thinking to enter the field of accounting.
Accounting still a good career in 2026? Looking for advice from actual accountants in the USA. I'm thinking about studying accounting, but honestly, I'm very scared and unsure whether I should do it or not. I already have an associate degree in architecture, but the truth is that I didn't enjoy architectural work, so I decided not to continue in that field. Considering my personality and the fact that English is my second language, I'm thinking about switching to accounting because at 33 years old, I'm looking for a more stable career.
So now let's talk about a job that I recently advertised and I filled at my role for a staff accountant, uh, in June of 2026. Um, and let's talk about this person, what they're doing, uh, what hasn't changed because of AI and what changed because of AI compared to, say, 5 years ago. All right, so let's talk about parts of the job that did not change, that are the same. So on a daily basis, they have to do some things that exist from before. So for example, reconciling bank accounts. So they have to get the bank statement, reconcile it to the books. They have to reconcile in the same way credit card statements to the books. They have to post cash transactions. So cash comes in through an automatic feed to ERP. They still have to go in and match it to either cash receipt or cash spent. The AI is doing some categorization. However, you still have to look at it from a business perspective and decide whether it's correct. You still need that human judgment as a review of what the AI is doing. So again, review a general ledger categorization, review customer invoices. So AI is able to create customer invoices now in many modern systems. However, because this is something that's sensitive, is going to a customer, uh, they will do a financial decision, meaning payment, based on it. You still need some sort of a human to review it. So that's what they're doing. They're reviewing AI-generated invoices. They're reviewing flux analysis. So flux analysis, by all means, now it's much easier than before. Many of the accounting systems, including QuickBooks, will generate a flux analysis for you. But you need the human to review it, even though there's commentary sometimes even being spit out by the system. But the commentary for the most part is inaccurate, and it's only commenting on the change in the numbers but not looking beyond it and the business itself like a human would, because the human is able to connect the story, right? I still need the staff accountant to mark down my checklist. So we have a finance close checklist that we go through for closing the financial period. I still need them to kind of go through it with their human judgment, and decide what is complete, what is not complete, right? After they're doing that, after they're done with that, I can go in and have a review as a controller and see from my own judgment as well whether I'm satisfied with the level of how each task is done. Okay, now let's talk about the parts of the job that changed because of AI. This is the more interesting part that you want to listen to. I also want to make an announcement, uh, because I've been working hard over the last few weeks on something new that you guys will be excited about. Uh, many of you have taken my courses, uh, but courses are video lectures, right? You're listening to me and watching me doing things. But now, for the first time, I'm going to give you something here. I'm going to show it here for the first time. Uh, it's called Ledger Lab right now, but that might change in the future, where you can go in and become the employee. Um, you're an accounting staff and you're going in, um, learning about the company, meeting the team. So as you see here, you get assignments. So you go in, you go through an orientation from the controller, you receive your first task. So you go to your assignments, you complete your accruals, your reconciliations in an ERP environment. So this is a simulated ERP environment. And then beyond that, you can go to the financial statements and look at the impact of the entries that you're making to the financial statements. You can download them, look at how trial balance links to everything else, the bill of materials, the vendor, customers. This is just like how it would look like if you are working in an ERP environment. So this is something that I've been building. It's going to be available in beta mode in early August 2026. When it's ready, I'm going to leave a link down below. So be on the lookout for that. If you are on my email newsletter, you will get a notification with that as well. Okay, now let's talk about the parts of the job that is changing because of AI. So the biggest part that's changing is AI agents. Right now we are using AI agents to do a variety of things, mainly fill in the gaps into the things that ERPs and accounting softwares are unable to do. That's mostly analysis. So to give you an example of that, the marketing department needs a breakdown of their spending by conference. You could do that in ERP because you could assign a project to your expenses, but that has some limitations. Sometimes your credit card provider or credit card website doesn't have the same field of project, so you're unable then to track expenses by project. You could do that with an AI agent where you can download the general ledger for a specific period, and because the ledger has dates and descriptions, you're able to then create a summary by event or conference. So you fill in the gaps of where ERP is unable to do the work, uh, today. We use AI agents to fill in documents. So for example, just last week I received a document from a customer that is asking for a diversity and inclusion PDF to be filled out. They basically just want to know whether we are a company that believes in diversity and inclusion And whether we have diverse ownership behind the company and things like that. So, uh, before I would go in, uh, open that PDF, maybe 3 to 4 pages, and just begin to fill it out. And that may take me a whole hour, maybe just thinking through the answer. But now with the AI agent, I can tell it, uh, based on everything you know about the company, uh, because I've been chatting with the agent for a while, um, and here is maybe some additional information like address and phone numbers and things like that. "Fill out this document for me and leave me some of the fields editable just so for me to review as a controller before I send." Cutting a whole hour of work right there. We use it in bank reconciliations. So for example, if you get your bank statement and you're trying to reconcile it to your ERP or QuickBooks and you find a difference between the two and you're unable to track down which, which transaction exists on one document and not the other, it's not clear to you. You could easily download that reconciliation from your ERP or QuickBooks and get the bank statement and upload the two together into the AI agent and tell it to find which transaction exists here but not here and vice versa. And that will give you an idea like, you know, what's happening. Maybe an error exists on a credit card that is not translating into the ERP or some transaction didn't make its way and then you can figure it out that way. We also use AI as a solution in Excel when we can't come up with a formula in Excel that can do what we need it to do. We can give a screenshot to AI and ask it like, what do you think here is the right way to go? Or you could upload the entire Excel workbook. As long as you're using an AI agent, of course, that has some business data security and you know that your IT department, if your company is big enough to have an IT department, clears that AI agent to be used, of course, for data security and all of these things. So what are we saying here? We're saying that all of the careers are being impacted— law, engineering, architecture, medicine. Um, there is just shifting around of what people do. At the end of the day, what AI is doing to accounting, if you think about it, is that this person that I hired is doing much less of the sort of the bean counting or the nitty-gritty sort of data entry mode type things. The role is being elevated more to become the true role of an accountant, which is an advisor to the business and not just a number cruncher. So this is what I see now in the summer of 2026. Uh, could it change soon? Yes. If it does, I will make another post and, and talk about it in detail like I talk about it here. So if you know someone who is considering accounting and wanted to know sort of from a controller what is happening in the market, to the jobs of accountants, share this video with them, give it a big thumbs up, that would help the video. And be on the lookout in my simulated ERP environment that's going to come out in August of 2026. Thank you for watching, and I'll see you in the next one.
