Most advice about automating a tax practice says the same two things: Start with something repetitive and start with something low judgment. That's true, and it's already become commonplace everywhere.

For example, if you pick a task frequent enough that fixing it pays off within a season, not a year, that's a smart move. That's why tasks like entering W-2 and 1099 data is a common first choice for that reason. And picking a task where the judgment involved is thin, even if an experienced person has always done it, is also a good idea — for instance, copying figures from a source document takes almost no judgment.

The Thomson Reuters Institute's recent 2026 State of Tax Professionals Report backs this up directly. More than half of respondents cite a lack of time and resources, and 47% cite cost of implementation, as their top barriers to automating more of their work. If time and money are both scarce, the tasks you pick first needs to earn their keep fast. That's the easy part — but here's what usually gets skipped.

While tackling repetitive and low-judgment tasks first may be smart, that only gets you into the right neighborhood, but it doesn't tell you which house to walk into. Two more questions matter just as much, and almost nobody asks them first:

1. Would you actually notice if it went wrong? and
2. Is the process behind it consistent enough to automate?

Would you actually notice if it went wrong?

This first question separates a safe automation done early from a risky one, and it has nothing to do with how repetitive or judgment-light a task may be. For example, take two tasks that both look reasonable under the standard advice. The first is pulling numbers off a W-2 into your tax software. If the tool misreads a digit, you catch it in seconds, because you're looking directly at the source document. The second is drafting a client-facing explanation of a tax position. If the tool gets a small detail wrong, nobody may notice until a client asks a follow-up question, or worse, until the it's already been sent out to all clients. Both tasks are repetitive, and both involve modest judgment; however, the first fails quietly, while the second fails loudly.

Most firms treat each automation decision as a fresh puzzle, which is part of why the effort stalls after the first attempt.

This isn't hypothetical. Thomson Reuters Future of Professionals Report 2026 action paper for tax and audit firm leaders found that more than one-third of tax professionals say they already use AI tools that their firm hasn't formally approved. Any of that so-called shadow AI use that touches client work leaves a gap, in which there's no record of what the tool was given or whether anyone checked its output. That's exactly the kind of gap a quiet failure slips through. Pick your first task so checking it takes seconds, not a second look weeks later.

Is the process behind it actually consistent?

Here's a test worth running first. Ask three people on your team, separately, how they currently manage the task. Three different answers means you don't have a task to automate yet. Indeed, you have three tasks pretending to be one.

This shows up constantly in small practices. One person formats workpapers a certain way because that's how they learned it. Another does it differently because a different partner trained them. And a third improvised because nobody trained them at all. Automating any one version just locks in whichever method happened to get picked.

The State of Tax Professionals Report found that only about half of tax professionals describe their firm's core processes as consistently standardized. That's not a criticism. In a small firm, standardization often loses to whatever gets the work out the door fastest during busy season. However, that also means the honest first step, before automating, is sometimes just deciding on one method of doing a task and writing it down.

For example, say your firm sends the same document request checklist to every new individual tax client. Right now, one person copies last year's email and edits it by hand, another starts from an outdated template, and a third writes it fresh each time.

While tackling repetitive and low-judgment tasks first may be smart, that only gets you into the right neighborhood, but it doesn't tell you which house to walk into.

If you run it through both questions before it touches any software, you might make better automation decisions.

First, on error visibility, this task passes easily. If the automated version misses an item, you'll see it the first time a client asks about it. Cheap to catch, cheap to fix.

On consistency, it fails, at least today. Three versions means there isn't one process to automate yet. Pick the version you actually want every new client to receive, write it down, and use it by hand for a few weeks before automating it.

Use the same two questions next time

Once the checklist example works, you're left with a method, and the next potential automated task will take less thought to evaluate. Say the next idea is having a tool draft the cover email that goes out with a client's finished return. Would you notice if it went wrong? Probably not right away. A slightly off tone or missing detail is easy to miss before it's sent, and the client may say nothing even if they do notice. That's a quieter failure than the checklist, so the fix is a mandatory review step before anything goes out, at least for the first few weeks. And that's better than a rule you add later after something slips.

Is the process consistent? Likely not, since what goes in that email tends to vary by client and by whoever's sending it. The fix is the same one as before: Decide on the one version of that email you actually want going out, write it down, and have everyone use it by hand for a few weeks before you hand it to a tool.

And voilà! Two potential automated tasks evaluated and resolved in the time it used to take to think through one.

Most firms treat each automation decision as a fresh puzzle, which is part of why the effort stalls after the first attempt. Asking the same two questions each time turns it into a habit instead.

You can learn more about the challenges of AI adoption in the tax, accounting & audit industry here‍