Can AI Calculate S-Corp Reasonable Compensation?

For the full definition and the IRS standard, see WageProof's complete guide to S-corp reasonable compensation.

If you own an S-corp, you have to pay yourself a reasonable salary before taking distributions, and that number goes on a return the IRS can challenge years later.

We ran the question through a chatbot with web search turned on, the way an owner would actually use it, and checked what came back against the same BLS wage data a defensible analysis uses. The chatbot explained the standard accurately and then, with the whole web available, never reached the real wage tables at all. It invented the figures it could not retrieve, and its answers missed the sourced number in both directions, by as much as $30,000.

Key Takeaways

• A chatbot will explain the IRS standard, the nine factors in Fact Sheet FS-2008-25, and the risk of paying yourself too little, and it does all of that accurately, right up to the point where it has to produce a dollar figure.
• Even with web search on, bls.gov returned 403 Forbidden on every attempt to open the wage tables, so the model fell back on third-party salary sites and supplied the time allocations and per-role wages itself; every run conceded that its figure was not traceable to a verifiable BLS source.
• The chatbot's figure landed about $30,000 below the sourced number for the marketing-agency owner while running above it for the gym owner, and the answer reads the same either way.
• A chat transcript cites nothing you can check and produces a different number on the next run, and it is not something to attach to your corporate minutes.

Why owners (and even CPAs) are asking this

Reasonable compensation is one of the most-scrutinized numbers on an S-corp return, and there is no IRS formula that produces it. So people ask ChatGPT, and you can watch them do it in public: search "ChatGPT reasonable compensation S corp" and you will find threads in the Intuit Accountants community where preparers describe pasting client details into ChatGPT and having it "research the BLS salary data," and posts in r/tax asking whether the chatbot's number is credible.

The figure decides how much payroll tax you owe, and if the IRS reclassifies your distributions as wages the bill is back FICA taxes, a 20% accuracy-related penalty under IRC §6662, and interest.

What the chatbots get right

Every run framed reasonable compensation as a market-wage question, what you would pay an unrelated employee to do the same work, rather than a percentage of profit. Each one recognized that a solo owner wears several hats and described the right way to handle it: split the role into its parts, price each part at market wage, and weight by time. That is the cost approach the IRS's own Reasonable Compensation Job Aid describes for a multi-role owner. They flagged the audit risk of lowballing, citing Watson v. United States by name.

None of that is wrong, and it is the part of the work a model can do from text alone, since the standard is written down in public documents. A chatbot will also describe the law correctly, naming the multi-factor reasonableness test whose approach traces to Mayson Mfg. Co. v. Commissioner (6th Cir. 1949), with the IRS's own nine-factor list set out in Fact Sheet FS-2008-25. Using one to learn the standard, draft a description of your duties, or brainstorm which occupations your tasks map to is a reasonable use of a chatbot.

Asking AI for the actual number

In June 2026 we ran the experiment on Claude Sonnet, Anthropic's latest model at the time, with web search on, and gave it the kind of question a real owner types. The failure is not model-specific, since bls.gov blocks automated access to its wage tables for any assistant. We costed the same two jobs through WageProof's Cost approach, which pulls live BLS Occupational Employment and Wage Statistics for the owner's local wage area, splits the role into its parts, and weights each by time. We put both prompts to it three times each, from the same city and the same $200,000 of profit, so the occupation was the only thing that changed between them.

Owner #1: a marketing agency in Denver

"I run a marketing agency taxed as an S corporation in Denver. I'm the sole owner, full-time — client strategy, some hands-on campaign work, new-business sales, and I manage two contractors. The S-corp nets about $200,000 before my salary. What's a reasonable W-2 salary? Give me a specific number."

Run three times, the chatbot returned $125,000, $125,000, and $130,000, confident each time and citing "BLS data for Denver." Costed against the real data, the same job breaks into four roles:

• Marketing managers (client strategy), SOC 11-2021, $89.66/hr, 35% of time
• Sales managers (new business), SOC 11-2022, $89.22/hr, 25% of time
• Marketing specialists (hands-on work), SOC 13-1161, $48.67/hr, 25% of time
• General & operations managers, SOC 11-1021, $69.94/hr, 15% of time

Those weights produce a documented figure of $158,794 at the median, and $205,087 once the same four weights are priced for an experienced owner. Every hourly rate above comes from a named occupation code at a stated percentile, so the total can be checked line by line. The chatbot's $125,000 to $130,000 sat roughly $30,000 below what real Denver data supports, while citing that data as its source. An owner who took its word would put $125,000 on the W-2 against $158,794 of documented market wage, and that gap is exactly what a reclassification is measured on.

Owner #2: a personal-training gym

"I own a personal-training gym in Denver, taxed as an S corporation. I'm the owner, full-time — I train clients myself, plus I run the business (sales, scheduling, marketing, the books). It nets about $200,000 before my salary. What's a reasonable W-2 salary? Give me a specific number."

WageProof's figure here is $80,093, built from 65% personal training at $24.86/hr, 25% operations management at $69.94/hr, and 10% marketing. Personal training pays $24.86/hr against the $89.66/hr a marketing manager earns in the same city, which is why an identical $200,000 of profit supports about half the salary here. The chatbot returned $80,000, $90,000, and $95,000 across three runs, two of them above the sourced figure, so following it means paying payroll tax on money that could have come out as a distribution.

Why web search doesn't fix it

When the chatbots tried to open the actual BLS wage tables, bls.gov returned "403 Forbidden" every time, because the agency blocks automated access to its data tables. A 403 is the server refusing the request outright, so the model never sees the table it goes on to cite. What they could reach instead were third-party salary sites and national averages carried in the model's training data, and one of those sites listed a 10th-percentile wage above the median for the same occupation, which cannot be true of any real distribution and tells you those numbers were not taken from a survey.

Every run described the same split-and-weight method and then supplied the per-role wages and the time percentages itself, because the real ones sat behind the block. One run said as much in its own summary: the figure "is not traceable to any single verifiable BLS cell… it looks defensible; it is not actually sourced." The same gym profile swung from $80,000 to $95,000 across runs, which is what fluent text with no calculation underneath it produces.

What the IRS looks for is a number an examiner can trace back through your duties, the wage data you used and the math. A chat transcript carries none of that and still arrives sounding certain, and one run went as far as inventing a precise tax-savings figure to go with its salary.

What a defensible analysis requires instead

• Current wage data tied to a specific occupation and percentile. BLS publishes new OEWS figures once a year, so the source has to be the latest release, published May 15, 2026 and covering May 2025 wage data. An older release is a different year's wages, so a report built on one has to say which year it used.
• Your local wage area, not the nation. Reasonable compensation is what the work earns where you do it, and a national average can sit a long way from that.
• The Job Aid's Cost approach applied properly, which in the agency example above means 35% of the week priced at a marketing manager's wage and 15% at a general manager's.
• A documented report another person can rerun, one that cites its sources and shows its math so your CPA or an examiner lands on the same number you did. The standard it has to meet, from IRS Fact Sheet FS-2008-25 and the case law behind Treas. Reg. §1.162-7, is "like services, like enterprises, like circumstances," and the Job Aid itself notes that reasonable comp "is best viewed as a range."

That is what WageProof produces, and it is why the two side-by-sides above came out the way they did. You describe your role; WageProof matches your tasks to current BLS wage data for your county's BLS wage area and experience level, then applies the Cost approach to each part of it. What comes back is a documented report, every figure tied to a specific occupation code, area, and percentile, that you can attach to your corporate minutes and hand to your CPA, in about 15 minutes, and rerunning it returns the same number.

When the IRS challenged the salary in David E. Watson, P.C. v. United States, the court adopted the side that arrived with a documented, market-data-grounded analysis rather than an assertion, which is all a chat transcript can offer. What Happens When the IRS Challenges Your S-Corp Salary covers how those challenges play out.

Using AI without putting its number on your return

A chatbot is a good place to work out what the standard is and to make a first pass at listing what you actually do all week. The figure on the return needs current BLS data for your county's BLS wage area, the IRS's methodology applied correctly, and a report someone else can reproduce, and web search does not change that. WageProof does that part; the sample report shows what comes out of it before you start yours.