Use case

Estimate the per-task and per-month cost of deploying autonomous AI agents.

Autonomous agents — planning loops, tool use, multi-step execution — consume 3–10x the tokens of a comparable interactive prompt. Modeling agent cost accurately is the single most important AI budgeting task for 2026 rollouts.

Tokens / event

20K – 200K

Events / user / day

5 – 50

Typical cost range

$0.10 – $3.00 per task

Recommended models

3

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Embedded in core workflows. Mixed adoption.

AI-assisted tasks

3 / 3

Annual estimate

$15.2K

Total token OpEx for 50 employees · Claude Sonnet 4

Tokens per employee / year54.00M
Total tokens / year2.70B
Input tokens2.11B78%
Output tokens594.00M22%
Cost per employee / year$304.56
Avg daily tokens / employee225.0K
Blended price$3.00 in · $15.00 out / 1M tokens
Working days assumed220
Task coverage100%

Recommended models for this workload

Frequently asked questions

Why do AI agents use so many tokens?

Agents re-read their full context on every planning step, accumulate tool outputs into the conversation, and often perform 5–20 LLM calls per user-visible task.

How do I control AI agent cost?

Cap planning steps, summarize working memory, route subtasks to efficient models, and cache tool outputs aggressively.

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