Back-Office AI ROI Calculator
Invoices, forms, approvals and reconciliations rarely make the AI keynote, but they are where research keeps finding the money. The calculator below prices your team's document work. Set it to your numbers.
The preset opens with 3,000 invoices a month, 6 minutes of an operations person's time per invoice at 35 euros an hour, 2,000 input and 500 output tokens per invoice and a person checking one in four, against an 18,000 euro representative build. The review share is higher than for support on purpose, because back-office work carries compliance checkpoints that stay human.
Your numbers
With taxes and overhead the hour costs €16.25.
Advanced · minutes per task, build, hosting, tokens
Since you opened this page, the task has cost
The same day, two ways
At 3,000 invoices a month, that is 144 a working day. A person spends 6 minutes on each.
Each square is one invoice. The gold sliver is the model writing all 144 answers, about 6 seconds each. The hatched part is the person reading 25 of every 100 before they go out.
Twelve months, the build paid once
The build pays for itself in 41 days. After that every month keeps €4,379. Twelve months, €46,547.
Out of 100 answers, how many does a person read?
Click a square. This is the honest number in the whole calculation, and it costs more than the model does.
Honestly, it barely matters
Seven models at list price, per invoice with the same checking. Cheapest to dearest, the whole price list fits in €0.0194. The SaaS agent billed per resolution is 5.9× away.
With Claude Sonnet 5.5 the tokens are €0.0099 of the €0.15 per invoice. The rest is the person reading. Pick the model for quality, decide the checking for cost.
Your inputs and published prices. Nothing else.
6 min / 60 × €16.25 = €1.63(2,000 × €1.84 + 500 × €9.20) / 1M × 1.2 = €0.009925% × 2 min / 60 × €16.25 = €0.14(3,000 × (€1.63 − €0.15) − €60) × 12 − €6,000 = €46,547All formulas, model prices and task defaults
Every formula with your values
6 min / 60 × €16.25 = €1.63(2,000 × €1.84 + 500 × €9.20) / 1M × 1.2 = €0.009925% × 2 min / 60 × €16.25 = €0.14(3,000 × (€1.63 − €0.15) − €60) × 12 − €6,000 = €46,547€6,000 / €4,379 a month = 41 days(€6,000 / 12 + €60) / (€1.63 − €0.15) = 379 a monthPublished list prices, USD per million tokens
Prices as of 2026-10-21. Copied from the vendors' pricing pages on that date. Check the linked page before you sign anything.
| Model | Input | Output | Source |
|---|---|---|---|
| Claude Haiku 5.5Anthropic | $0.1 | $0.5 | Pricing page ↗ |
| Claude Sonnet 5.5Anthropic | $2 | $10 | Pricing page ↗ |
| Claude Opus 5.5Anthropic | $4 | $20 | Pricing page ↗ |
| Gemini 3.8 FlashGoogle | $0.75 | $3.75 | Pricing page ↗ |
| Gemini 3.1 ProGoogle | $2 | $12 | Pricing page ↗ |
| GPT-6 LunaOpenAI | $0.1 | $0.5 | Pricing page ↗ |
| GPT-6 SolOpenAI | $2 | $10 | Pricing page ↗ |
| Intercom Fin (per resolution)SaaS, per resolution | $0.99 / task | Pricing page ↗ | |
What each task assumes
| Task | Minutes | Tokens in / out | Checked | Build | Saving a year |
|---|---|---|---|---|---|
| Support ticket reply | 8 | 1,200 / 400 | 20% × 3 min | €4,500 | €90,641 |
| IT request (reset, access) | 12 | 900 / 300 | 15% × 2 min | €5,000 | €51,222 |
| Lead research and qualification | 15 | 2,500 / 600 | 30% × 4 min | €3,500 | €31,543 |
| Sales email or proposal draft | 40 | 3,000 / 1,200 | 100% × 8 min | €3,000 | €27,408 |
| Invoice parsing and entry | 6 | 2,000 / 500 | 25% × 2 min | €6,000 | €46,547 |
| Email classification and routing | 2 | 600 / 100 | 5% × 1 min | €2,500 | €47,247 |
| RFP / security questionnaire answer | 25 | 4,000 / 800 | 60% × 6 min | €5,000 | €8,148 |
| Payment reminder and collections touch | 6 | 1,500 / 300 | 30% × 2 min | €4,000 | €21,486 |
| Your own task | 10 | 1,500 / 500 | 30% × 3 min | €4,000 | €24,749 |
Working estimates from projects delivered in 2025 and 2026, not benchmarks. Every number is editable above. The saving uses your salary, currency and model.
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What AI actually automates in the back office
Modern document AI goes far beyond OCR templates. A typical first build covers:
- 01Structured extraction from invoices, POs and forms, with a confidence score per field and a human review queue for anything below threshold.
- 02Three-way matching of invoice, order and receipt, so people only see the exceptions.
- 03Approval chasing with reminders, escalation and status tracking that ops staff currently do by forwarding emails.
- 04Inbox triage for shared mailboxes that classifies, extracts, routes and drafts the routine replies.
- 05Report assembly from systems that do not talk to each other, delivered before the Monday meeting instead of during it.
Realistic ranges to expect
Document pipelines are among the most reliable AI investments. Volumes are steady, formats repeat and accuracy is measurable per field. The calculator prices the human check explicitly instead of applying an automation rate. Raise the review share to 40 or 50 percent if your documents arrive as scans and photos rather than digital files, and plan around that number.
What the research says
Three dated, sourced findings on where back-office automation actually pays:
MIT's Project NANDA reported in July 2025 that about 50 percent of enterprise GenAI budgets go to sales and marketing while back-office automation often yields better ROI, with successful deployments eliminating 2 to 10 million dollars a year in outsourced processing costs.
MIT Project NANDA, State of AI in Business 2025, July 2025 ↗
Deloitte's 2022 global intelligent automation survey of 479 executives found organizations that scaled automation achieved an average cost reduction of 32 percent, with a typical payback period of about 22 months.
A Deloitte study for Docusign published in April 2026 found organizations using agentic document workflows report nearly 30 percent higher ROI, with HR teams reclaiming 45 percent of the time spent on agreements and legal teams 37 percent.
How to read your result
Note the tension in the research. MIT found 95 percent of GenAI pilots showed no measurable return, yet the winners cluster exactly here, in documents and process. The difference is scope. A pilot that "explores AI for operations" fails, while a build that extracts three fields from one invoice format and posts them to your ERP pays for itself and earns the next project. Use the conservative year in this calculator as your business case and the headline saving as the goal.
Back-office ROI questions
01How accurate is AI document extraction?
On digital PDFs, extraction of standard fields is highly reliable; scans and photos are harder. That is why we ship every pipeline with per-field confidence scores and a review queue: the system knows what it is unsure about and asks a human.
02Is this just RPA under a new name?
No. Classic RPA replays clicks and breaks when a layout changes. LLM-based extraction reads the document the way a person does, so a new invoice template degrades accuracy slightly instead of halting the pipeline.
03What about our data and GDPR?
Pipelines run in your accounts and can run fully on-premise for sensitive documents, so nothing leaves your network. We are an EU firm and build to GDPR by default.
04What does a document automation project cost?
Workflow and document automation starts around 2,000 dollars for a single pipeline; the task default assumes 18,000 euros for a fuller build across several document types. The figure is fixed in writing after a free scoping call.