Enterprise AI agent pricing in 2026 comes in four shapes: per seat, per conversation, per outcome, and per role. The published numbers run from $200-a-month credit packs to contracts priced like a mid-level hire. None of them means anything until you put it next to the cost of the work it offsets, and that cost is not on your software budget. It is the burdened cost of a role, multiplied by the share of that role that is defined procedure.
Most pricing pages are built to keep you from making that comparison.
The burdened cost of a role is the salary plus everything else it takes to employ the person: employer taxes, benefits, insurance, overhead. According to the Bureau of Labor Statistics' Employer Costs for Employee Compensation release (March 2026), benefits account for 30.1% of total employer compensation costs in private industry, which puts the real cost of an employee at roughly 1.4 times wages.
The market has not settled on a unit. Salesforce publishes a per-conversation rate for Agentforce at around $2, billed whether or not the conversation resolves anything, and SaaStr counted at least three Agentforce pricing models running simultaneously in 2026. Microsoft sells Copilot Studio capacity in packs of 25,000 credits for $200 a month, and per its licensing documentation an autonomous agent action consumes 25 credits or more, so an agent that acts rather than answers burns capacity fast. Sierra publishes no rates at all: contracts are outcome-based and custom-quoted. And a newer class of vendors prices the way a hiring manager thinks. Published AI sales-development pricing indexes (2026) put 11x contracts between roughly $36,000 and $65,000 a year, which is not a software number. It is a junior-headcount number.
| Pricing model | Example (2026) | What you are actually buying |
|---|---|---|
| Per seat | Microsoft 365 Copilot at $30 per user per month | AI assistance for a human who still does the whole job |
| Per conversation or credit | Agentforce around $2 per conversation; Copilot Studio at $200 per 25,000 credits | Every interaction, metered, resolved or not |
| Per outcome | Sierra, custom-quoted, no published rate card | Resolutions, at a rate you negotiate without a benchmark |
| Per role | AI sales-development workers published at $36,000 to $65,000 a year | A job, priced against the hire you did not make |
The drift across those rows is the story. Agent pricing is migrating off the software budget and toward the headcount line, because that is where the value sits and every vendor knows it.
Take an AP clerk at $60,000. Apply the BLS private-industry ratio and the burdened cost lands near $84,000 a year. Now be honest in the other direction, because an agent does not do the whole job. It does the procedural share: the part with written steps, named systems, and a defined sign-off. Call that 70% for a queue-driven AP role, and your number will differ. The procedural share of that clerk is worth about $59,000 a year.
That is the denominator. Not the salary, and not the software line.
An agent that completes a task a person still has to approve has not saved the whole task. When we built the case-study math for Maya Workforce AI, we wrote the honesty rules into the computation itself. Hours saved are bounded to tasks the agent actually completed, minus the human minutes still spent approving them. Cost per task carries that residual approval labor on the agent's side of the ledger, not just the token spend. A deployment where the agent escalates everything shows near-zero savings, because near-zero is what it saved.
Nothing in that math credits work that never happened. The base unit is a completed task, not a task a person might hypothetically have done.
If a vendor quotes savings equal to a full salary, ask which line of their math subtracts the human approval time their agent still consumes. If the answer is a pause, you are looking at a deck number, not a procurement number.
Maya prices the way the fourth row does, because the other rows meter the wrong thing. An agentic employee is scoped to one role: a job description, credentials into the systems that job touches, written procedures, and a person who owns the approvals. The implementation is a fixed-scope engagement, and the annual agreement is set against the burdened cost of the role, never per seat, so the comparison you are making is the one on this page. AP, HR, IT service desk, and marketing ops deploy fastest because those connectors and procedure sets already exist, but the model is role-agnostic: if the procedural share of a job can be written down, it can be authored as a role. The Maya product page has a calculator that runs this burdened-cost math against your own numbers.
If your problem is narrower than a role, a ticket queue rather than a job, the math changes shape. I walked through that version in what IT helpdesk automation actually costs and the AI helpdesk ROI math.
Anywhere from $200 a month in platform credits to $65,000 a year for a role-priced digital worker, depending on the pricing model. Salesforce Agentforce runs around $2 per conversation, Microsoft Copilot Studio sells 25,000-credit packs at $200 a month, outcome-based vendors like Sierra custom-quote every contract, and role-priced agents publish in the $36,000 to $65,000 a year range. The model matters more than the sticker price, because each one meters a different thing.
For the procedural share of a role, usually, but the honest comparison subtracts what the agent does not do. Put the agent's all-in cost against the burdened cost of the role times its procedural share, then subtract the human time still spent on approvals and escalations. Any vendor math that credits the agent with a full salary is overstating the case.
Salary plus employer taxes, benefits, and overhead. Bureau of Labor Statistics data from March 2026 puts benefits at 30.1% of total employer compensation costs in private industry, so a workable rule of thumb is 1.4 times base salary. A $60,000 role costs the employer roughly $84,000 a year.
A seat prices access for a human, and an agent is not a human using software. It does a defined share of a job. Pricing per role puts the cost next to the headcount line it offsets, which is the comparison a department head is actually making, and it removes the incentive to meter every conversation whether or not it resolved anything.
The Maya Workforce AI product page has the burdened-cost calculator, the pricing model, and the implementation path. Bring the role you are thinking about and the systems it touches.
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