Every accountant I talk to is excited about AI doing the work. Not one of them has asked the harder question: can you prove the AI got it right?

Agents categorize transactions now.

They draft journal entries. They reconcile accounts. They make changes faster than any human could.

But how do you know it's accurate?

How do you prove to a client that every number was reviewed and compliant? How do you show an auditor that an AI-generated entry followed the same logic a senior accountant would use?

"The AI did it."
This is not an answer in accounting.

Every number needs a trail.

Every change needs a reason.

We built Puzzle around this problem.

Not just AI that does the work. A system that proves the work was done right.
Immutable audit trails. Full traceability from GL line to raw transaction. Every agent action logged. You can review it. You can reverse it.

The AI does the work.

The proof of accuracy is the product.

When every platform has AI, the one that can prove accuracy wins the accountant. And the accountant wins the client.

Speed was the old differentiator.

Proof is the new one.

P.S. Excited to share we just launched AI Close for Accountants. The first agent builder built into the general ledger for accounting firms: https://lnkd.in/gv6KXbP9

I've been using AI heavily in finance for a year. Here's what I've found actually matters:

1️⃣ If your accounting system doesn't connect easily with an external AI (ChatGPT, Claude, etc.), you're using the wrong accounting system. Built-in AI tools in accounting systems like QBO are rarely as capable as the real thing.

2️⃣ Know the privacy risks. My rule: strip out identifying information before uploading any document.

3️⃣ Treat it like a new staff accountant. You have to check its work. You have to train it. It will make mistakes.

4️⃣ Direct connectors to Google Drive or cloud storage are hit or miss. If accuracy matters, export the reports and upload manually to the AI model.

5️⃣ Before you review anything, ask it to double-check its own work first. It catches its own errors more often than you'd think.

6️⃣ Reconciliations and matching tasks are where it shines. Add agents into the mix, and you're automating a significant chunk of staff-level accounting work.

7️⃣ The future belongs to finance professionals who understand how these models think, know roughly what the answer should look like, and can verify the math. Your experience-based gut instinct matters more now, not less.

8️⃣ Cash flow forecasting is where I'd start for most businesses. It's the single highest-impact use case I've found.

9️⃣ For FP&A work specifically, Claude is the clear winner — and worth the paid upgrade.

🔟 Information overload is real. My fix: ask it to cut the output by 50%, then ask it to simplify further. Forces it to distill down to what actually matters.

AI won't replace experienced finance professionals. But it will replace those who don't know how to use it.

#Finance #AI #Accounting #FPandA #CFO