★ Bookkeeper · agent or hire?
AI Agent vs Hiring a Bookkeeper: Cost Calculator
Bookkeeping is categorising transactions, matching them to documents and chasing what is missing. Agents are good at the reading and matching. The numbers must stay exact, so the arithmetic belongs in code and a person signs off the close.
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Presets are starting assumptions for a small team, not industry statistics. Change every number to match your reality.
The agent saves
$1,505 / month
Pays back the build cost in 10.0 months.
People only
$3.1K/mo
With agent
$1.6K/mo
Hours freed
48 h/mo
12 months, side by side
Cumulative cost. The agent line starts at the build cost.
| Month | People only | Agent |
|---|---|---|
| 0 | $0 | $15K |
| 1 | $3.1K | $16.6K |
| 2 | $6.3K | $18.2K |
| 3 | $9.4K | $19.9K |
| 4 | $12.5K | $21.5K |
| 5 | $15.6K | $23.1K |
| 6 | $18.8K | $24.7K |
| 7 | $21.9K | $26.3K |
| 8 | $25K | $28K |
| 9 | $28.1K | $29.6K |
| 10 | $31.3K | $31.2K |
| 11 | $34.4K | $32.8K |
| 12 | $37.5K | $34.4K |
Where the agent cost goes
- Work people still do$938
- Reviewing the agent$182
- Model usage$0
- Maintenance$500
Model cost per task: $0.0004 on GPT-6 Luna, for 1,050 agent tasks a month.
An agent that pays back in 10.0 months.
I build production AI agents with human review, guardrails and logging.
What the agent can and can't take
Good jobs for the agent
- Categorise transactions using your chart of accounts
- Match bank lines to invoices and receipts
- Chase missing receipts by email
- Explain why something doesn’t reconcile
Keep with a person
- Decide tax treatment of an unusual transaction
- Sign off the books
- Fix a mismatch it can’t prove
What review looks like: Auto-post only matches that are proven (amounts and references agree), queue the rest for a person, and have someone review the month-end close.
Good fit, bad fit
| Good fit if… | Not a good fit if… |
|---|---|
| Lots of small, similar transactions | Complex multi-entity or tax-heavy books |
| Documents arrive digitally | Paper-first processes |
| Your accounting system has an API | No accountant to own the close |
Risks to plan for
- A wrong number that looks right
- Miscategorised spend that distorts reports
- Sending financial data to a provider without the right terms
How the comparison works
The calculator compares two ways of getting the same tasks done each month: people doing all of them, or an agent doing a share while people do the rest and review the agent's work.
people only = tasks × minutes ÷ 60 × hourly cost
with agent = remaining human work + review time + model cost + maintenance
model cost = agent tasks × (input tokens × input price + output tokens × output price)
savings = people only − with agent
payback = build cost ÷ savings (never, if savings ≤ 0)
It only counts the share of someone's time spent on these tasks, so it answers “what does this work cost”, not “can I remove a job”. Model prices come from the LLM API Cost Calculator.
Worked example
The bookkeeper preset with the example salary of $60,000 plus 25% overhead, 1,500 transactions a month at 3 minutes each, the agent handling 70% and a person reviewing 25% of those:
| Line | Per month |
|---|---|
| People only | $3,125 |
| Remaining human work | $938 |
| Reviewing the agent | $182 |
| Model usage (GPT-6 Luna) | $0 |
| Maintenance | $500 |
| With the agent | $1,620 |
| Saving | $1,505 |
With a $15,000 example build cost, payback is 10.0 months. Notice how small the model cost is next to the human time that remains: review time and the share the agent can't finish usually decide the answer, not token prices.
Questions about this role
Can AI do bookkeeping accurately?
Do I still need an accountant?
What is a safe first step?
Is an AI agent cheaper than hiring someone?
Where do the model prices come from?
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More from the workbench
Fine print
Tools: on the house.
Engineer: by the hour.
The math was free. A reliable agent takes engineering, which is what I do.
I'm Himanshu, an AI and full-stack engineer. I build MVPs, AI agents and the growth plumbing around them for early-stage startups.