From Preparer to Reviewer: How AI Is Changing the First Years of Your Accounting Career
Earlier this month, Business Insider published an article about PwC’s plans for its new hires. According to their AI assurance leader, Jenn Kosar, junior staff will soon be working “almost instantaneously” as reviewers (more like managers) because AI will take over much of the routine, entry-level work. On the surface, this might sound like a win: skip the grunt work, fast-track to management skills.
But as someone who’s been a CPA for over a decade and teaches accounting at night, I see both sides.
Why This Is a Big Shift
Traditionally, your first years in public accounting were about doing—creating workpapers, tying out schedules, chasing down supporting docs, and yes, fixing mistakes over and over until the fundamentals became second nature. That repetition was the training ground. It taught you not only how to prepare good work, but also how to spot when something was wrong.
If you’ve never done a bank reconciliation yourself, can you really catch an error in one prepared by someone else, or by an AI model that’s confident even when it’s wrong? That’s the risk here.
The New Path: Supervising Before You’re Ready
If this industry-wide shift accelerates, you might spend your first year reviewing 20 reconciliations instead of preparing one from scratch. That could mean you get more exposure to higher-level thinking earlier, but it also means you miss the “muscle memory” that comes from preparation. And make no mistake—supervising without a solid technical foundation is like trying to coach a sport you’ve never played.
How to Build Your Skills in This New Environment
Even if AI or offshore teams handle much of the prep work, you can still develop your technical chops. Here’s how:
Don’t just sign off—verify. Pick a sample from the work you’re reviewing and re-perform it yourself. You’ll reinforce fundamentals and catch things you might otherwise miss.
Treat review comments as a goldmine. If a more experienced reviewer changes something you missed, figure out why—and make a note of it.
Ask to shadow the prep process. Even if you’re not the one doing it, watch someone else build the workpapers so you understand the steps involved.
Own the context. AI is powerful, but it doesn’t understand the “why” behind the numbers. You do. Always connect the dots between the data and the underlying business reality.
Seek feedback without fear. The best professionals don’t avoid mistakes—they learn from them quickly.
The Industry’s Bigger Question
For decades, staff and seniors had time to master their fundamentals before taking on significant review responsibilities. If AI and outsourcing remove most preparer-level work, we need to ask: Where will tomorrow’s senior accountants come from if no one is training staff accountants today?
The answer isn’t to reject technology—it’s to adapt our training models so technical skills and judgment grow together. AI can make you faster, but only experience will make you accurate.
Final thought: If you’re starting your career now, see AI not as a shortcut to skip the “boring” work, but as a tool that frees up time to learn more—to go deeper into the numbers, ask better questions, and understand the business behind the balance sheet. In the end, that’s what will make you not just a faster accountant, but a better one.