AI in CAS: The Real Constraint Accounting Firms Are Ignoring

✋Welcome to The CAS Cache, a newsletter designed to help accounting firms grow their CAS offerings in five minutes or less.

Disclaimer: Some links below support my writing of this newsletter, and some give you a deal.

Issue Sponsor 😎

Don’t outsource. Hire direct in the Philippines.

You can hire an accountant who works for you and only you. No middlemen. No ongoing fees. Just you and your team. Schedule a call with TeamUp now to learn how direct hire works.

Want to sponsor The CAS Cache? Reply to this email to get more details.

In the last article, I talked about the AI monkey pedestal problem. The idea that AI looks incredibly powerful in theory, but in practice, it still depends on the business owner to actually make it work.

I got a lot of great feedback on that one, which I appreciate. Most people agreed with the core idea. AI will be a great tool for firms, not a replacement. But a few of the pushbacks stuck with me, and I think they are worth working through.

One of those was Jason Staats’ videos showing how he is using AI for bookkeeping. If you have not watched them, I would. It is a really good look at what is becoming possible. AI agents are improving quickly, and workflows that felt unrealistic not that long ago are starting to look doable.

But watching it actually reinforced the original point for me more than anything else. The gap is not what AI can do. The gap is what actually happens in the real world.

The Monkey Problem

Because when you step into a client’s business, they are not thinking about building an AI accounting workflow. They are thinking about sales, employees, operations, and whatever problem is right in front of them that day. Stopping to upload receipts, clarify transactions, or explain why they spent money somewhere is already a challenge today. Wrapping that inside an AI system does not remove that problem.

That is still the monkey. And until that piece changes, AI bookkeeping will run into the same constraint. Not capability, but input.

Where AI Actually Breaks in CAS

This is where I think automation is a bit misleading right now. It is absolutely making bookkeeping more efficient, but it is also quietly reducing the level of detail in many cases. If transactions are being auto-categorized without receipts or context, the books can look clean while actually becoming less useful.

You see it all the time with something like marketing spend. It gets coded correctly, but that is where the story ends. No campaign, no goal, no expected return. And once that detail is gone, it limits everything you can do afterward.

Why AI Advisory Still Isn’t There

That is also why I do not think we are close to AI handling advisory, at least not in a way I would put in front of a client.

I have been playing around with the AI features in QBO and Fathom, and they are good at summarizing changes. They can tell you what is happening. Revenue is up, margins are down, and expenses have increased in a certain area.

But they still struggle with why.

And that is the part clients pay for in CAS. Why did it happen, and what should the client do next? That requires context, conversations, and an understanding of the business that goes beyond the numbers.

The AI Debate: Advisory vs Bookkeeping

There is also an interesting take I had a discussion with a colleague: that AI might figure out advisory before it fully solves bookkeeping. I get the argument. AI is very good at analyzing trends and comparing data across a large set of businesses, while bookkeeping depends on messy, inconsistent inputs.

But the two are more closely tied together than people think.

Advisory without detail is surface-level. If the data is not clean and complete, the insights will be limited, no matter how good the model is. AI might speed up parts of advisory, but it still depends on solid bookkeeping to be truly valuable.

How I Am Thinking About AI in Accounting

So for me, this does not change the direction. If anything, it reinforces it. Keep learning AI. Keep using AI. Stay ahead of where AI in CAS is going.

But do not move away from the fundamentals. Good bookkeeping and strong advisory still go hand in hand. If you can pair those with AI, that is where the real leverage is.

That is what I am personally working on right now.

Thanks for reading, Luke Templin!