What Does AI Cost per Employee in 2026?

At list price, a standard seat on the workplace AI tools that publish a price costs $19 to $39 a user a month in November 2026, and some plans bill use by the token on top. Microsoft lists Microsoft 365 Copilot at $30 a user a month paid yearly, and GitHub lists Copilot Business and Enterprise at $19 and $39. Across all AI spending for the year, including hardware, training and IT support, US firms expected an employment-weighted average of $2,068 per employee in 2026, according to a Federal Reserve Bank of Atlanta survey, while more than half of the firms expected to spend no more than $200.

How is AI billed: by the seat or by the token?

The first way is a seat: a fixed price for each person given access, charged every month whether or not that person uses the tool. The second is by use, counted in tokens. A token is the unit AI vendors bill by, roughly a piece of a word. Vendors charge per million tokens sent to the model and written back, at rates set for each model.

Many enterprise plans now combine the two. Anthropic lists Claude Enterprise as “Seat price + usage at API rates”, so each seat carries a flat fee and the person’s use is billed on top at the per-token rates developers pay. GitHub builds an allowance into each seat. Its billing documentation says Copilot Business includes 1,900 AI credits per user and Enterprise 3,900, and its plans page prices one credit at $0.01, so the allowance is worth the seat price. Credits are pooled across the organization, and admins decide whether use beyond the pool is allowed and paid for. Microsoft sells Microsoft 365 Copilot as an add-on seat and states that a separate license for a qualifying Microsoft 365 plan is required.

For a budget, a seat bill is known in advance and grows with the number of seats. A use bill grows with the work and the model chosen, and it can change from one month to the next.

AI license prices per user: list prices in November 2026

The table gives the list price of common seat products, each read on the vendor’s own page on November 13, 2026. Every price is per user a month in US dollars, before tax.

Anthropic and OpenAI also list a premium seat for heavier users, at $100 a month billed annually on both the Claude and ChatGPT Business pages. The fictional example below assumes Claude Enterprise.

What does usage-based AI add to the cost per employee?

Use is the part of the bill that changes from month to month. Anthropic’s pricing documentation lists Claude Sonnet 5.5 at $2 per million input tokens and $10 per million output tokens, and Claude Opus 5.5 at $4 and $20. Claude Fable 5.2, described there as for demanding reasoning, lists at $8 and $40, and Haiku 5.5, for high-volume tasks, at $0.10 and $0.50 for prompts up to 100,000 tokens. Input that the model reads again from a cache is billed at a small fraction of the input rate.

Two people with the same Claude Enterprise seat can therefore cost very different amounts. Take two assumed monthly volumes, priced at those Anthropic rates. A finance analyst who uses AI for drafting and analysis sends 3 million tokens and gets 0.5 million back on Sonnet 5.5: 3 × $2 plus 0.5 × $10 is $11. An engineer who runs a coding agent for much of the day sends 40 million tokens and gets 4 million back on Opus 5.5: 40 × $4 plus 4 × $20 is $240. The volumes are assumptions chosen for illustration. A company’s own figures come from its invoices and the vendors’ usage reports.

Worked example: AI cost per employee at a fictional 500-person company

This company is an example, invented for this article. Its headcounts, seats and token volumes are assumptions, priced at the list prices above, and the result is not a benchmark for what any company spends or should spend. Token use is priced at the standard input and output rates, with no discount for cached input.

The assumptions:

• Engineering, 60 people. GitHub Copilot Business at $19 and a Claude Enterprise seat at $20, plus Claude use of 40 million input and 4 million output tokens a person a month on Opus 5.5, which is $240. GitHub use stays within the included credits.
• Finance, legal and analysis, 40 people. Microsoft 365 Copilot at $30 and a Claude Enterprise seat at $20, plus 3 million input and 0.5 million output tokens a month on Sonnet 5.5, which is $11.
• Sales and customer support, 150 people. Microsoft 365 Copilot at $30.
• Managers, HR and office operations, 100 people. Microsoft 365 Copilot at $30.
• Field and warehouse staff, 150 people. No AI seat.
• The company already holds the Microsoft 365 plans that Copilot requires, so their cost is left out. Microsoft and Claude seats are priced on annual billing, GitHub per user per month, all before tax. The 100 Claude Enterprise seats are above the 20-seat minimum.

The monthly bill is $16,740 + $2,440 + $4,500 + $3,000 = $26,680, or $320,160 a year. Divided by 500 employees, that is $53.36 per employee a month, or about $640 a year. Divided by the 350 people who hold at least one seat, it is $76.23 a month. Seats account for $11,840 of the monthly bill and token use for $14,840, so use is 56% of it.

Engineering is 12% of headcount and 63% of the bill, while the 150 field staff have no AI tool cost. Use also makes the total less stable. If the engineers’ token use doubled to 80 million in and 8 million out, their use would cost $480 a person, the monthly bill would rise to $41,080 and the average would move to $82.16 per employee. That is an increase of 54% from a change in one group of 60 people.

The example covers the tools only. The Atlanta Fed figure in the next section also counts hardware, training and IT staff support, so the two numbers cannot be compared directly.

Why does the average AI cost per employee hide the spread?

The same skew appears between companies. In March 2026, researchers at the Federal Reserve Bank of Atlanta and their co-authors asked senior executives what their firms would spend on AI, counting software, subscription services, hardware, worker training and IT staff support. In results published May 6, 2026, the employment-weighted average was $1,358 per employee in 2025 and an expected $2,068 in 2026, after the highest answers were capped at the 99th percentile. Without that cap, the 2026 average was $3,108. More than half of the firms expected to spend no more than $200 per employee, while the top 10% planned to spend at least $2,800. The authors say this 14-fold gap points to “a highly skewed distribution of AI investment intensity.”

In the worked example, the spread comes from the mix of roles. Seat prices sit close together, and most of the gap comes from who holds a seat and how much use is billed on top. Neither a high average nor a low one says whether the money is well spent.

A cost per employee becomes useful once it is split by role and read beside two other facts: how much of the role’s work AI can do, and what the role produced over the same period. A high cost in a role where much of the work suits AI and output rose is a different finding from the same cost in a role where little of the work suits AI. Is your AI spend in the right roles? sets out that comparison, and Token use per employee covers what a usage count can and cannot show. How should a company set an AI budget per employee? turns the split into allowances by role. JobRoute shows spend by role from the usage reports of a company’s AI tools, beside each role’s task-by-task score and output measure: see AI spend by role.

What do surveys say about AI spending in 2026?

BCG reports AI spending as a share of revenue. Its Applied AI Index, released September 30, 2026 and based on a survey of 1,330 CxOs and senior leaders, found that AI spending had grown from about 1.7% of revenue in late 2025 to 3.3%. It also found that more than 80% of AI spending now sits outside enterprise IT. For a cost per employee, that suggests the IT budget alone will undercount, so tools that departments buy on their own budgets belong in the total.

Fewer companies can see the cost of each unit of AI work. Deloitte’s State of AI in the Enterprise survey of 3,500 leaders in 25 countries, published October 29, 2026, found that 71% track total AI inference and API spend, 51% track token volume and 44% track per-unit inference cost. Deloitte’s Costi Perricos said that “far fewer understand the unit cost underneath it.”