AI Agent vs Hiring: How to Compare the Real Numbers

Most owners weighing an AI agent against a hire compare a price tag to a salary. That comparison is wrong in both directions. It understates what the hire costs, and it says nothing about what either one returns.

We will not tell you what a hire costs at your company, because we do not know your band and neither does anyone quoting an average at you. What we can give you is the arithmetic, the sourced multipliers, and our own published price.

#The salary is not the cost

Base pay is the visible number, and it is not the number that leaves the business.

Take whatever you would actually pay and multiply it by about 1.4. That is the loaded figure: base pay plus the benefits an employer carries on top of it. Add recruiting, which SHRM puts at an average of nearly $4,700 per hire, paid before the person does a day of work. That line repeats every year, and it repeats again from the top if they leave.

Our Agents tier is $10,000 to set up and $500 a month per agent after that, which is $6,000 a year ongoing. Additional agents are $5,000 each. Those are published prices on our services page, not estimates.

Here is the one conclusion this arithmetic clearly supports. Load any professional salary at 1.4x and it clears $6,000 a year many times over, at every band we have seen. On the repeatable slice of a role, price is not the thing that makes this decision hard. Scope is. The rest of this piece is about scope.

#Cheaper is only half the claim

Cheaper matters only if the agent carries comparable work. On the repeatable slice, the drafting, the lookups, the data entry, the boilerplate, it does, and it does so around the clock.

That figure comes from a peer-reviewed study of a live deployment. Larger ones generally do not. It is also worth knowing where the average comes from: the same study found less experienced workers improved both speed and quality, while the most experienced saw very little change. An agent lifts the floor more reliably than it lifts the ceiling.

An agent does not replace judgment, relationships, or accountability. It takes the repeatable substance of a role, not the whole role.

#Run the return on your own numbers

#Why most AI buys still fail

Cheaper and capable is not enough. Plenty of companies buy AI and get nothing back.

The failure is rarely the model. It is treating AI as a tool you buy and log into, instead of a capability you implement into the real workflow and keep improving. An unowned agent is a cancelled line item. An owned one does the repeatable work you would otherwise be hiring for.

#The bottom line

Compare loaded cost to loaded cost using your own salary band. The multiplier on the hire is about 1.4x base plus recruiting, every year. Our side is $10,000 to set up and $6,000 a year ongoing, published and checkable.

The catch is symmetric. A hire fails if you do not manage them, and an agent fails if you do not implement it and keep improving it. The arithmetic only becomes decisive after the ownership question is answered, and that part is the actual work.

Scoping which hours are genuinely repeatable is where this decision is actually made. Here is how we approach that.

#Sources

• Employer Costs for Employee Compensation, March 2026 (U.S. Bureau of Labor Statistics): https://www.bls.gov/news.release/ecec.nr0.htm
• The Real Costs of Recruitment (SHRM): https://www.shrm.org/topics-tools/news/talent-acquisition/real-costs-recruitment
• Generative AI at Work (Brynjolfsson, Li and Raymond, Quarterly Journal of Economics, 140(2), 2025): https://academic.oup.com/qje/article/140/2/889/7990658
• Generative AI shows rapid growth but yields mixed results (S&P Global Market Intelligence, 2025): https://www.spglobal.com/market-intelligence/en/news-insights/research/2025/10/generative-ai-shows-rapid-growth-but-yields-mixed-results