Practice

Accounting & finance · Use cases

AI in accounting & finance: receipts, invoices, reporting

How accounting and finance teams use AI GDPR-compliantly: pre-capture receipts and invoices, extract data, prepare reporting — with real workflows, an example prompt, strict review limits and selection criteria.

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Who it is for
Heads of finance and controlling, accountants, tax clerks and finance operations
Impact
Less manual pre-capture — routine work supported, every posting-relevant statement reviewed by a human
Task
Pre-capture receipts and invoices, extract data and prepare reporting with AI — under strict human review
What it is about

What this use case delivers.

AI in accounting means using generative AI for the preparatory, recurring tasks in finance — extracting and structuring data from receipts and invoices, drafting text for reports and analyses, answering recurring questions about processes. Important: the AI supports pre-capture and preparation; every statement with legal, tax or financial effect must be reviewed and approved by a human. It runs GDPR-compliantly in the EU, without input being used to train the models.

How it works

A finance assistant extracts structured fields from uploaded receipts and invoices — supplier, date, amounts, tax rates, line items — and proposes a pre-capture that a human reviews and approves. For reporting it turns existing figures into understandable explanatory text and management summaries, without calculating the figures itself; those come from the audited systems. Recurring questions about posting and travel-expense policies are answered from the connected handbook with a source reference. Connectors and an API link permitted data sources. Because several leading models are available, you can pick the right one per task; an academy enables the team to use the AI as preparation and to double-check it consistently.

Concrete workflows

These steps are part of the implementation.

These recurring tasks can be covered with the same underlying pattern.

01

Pre-capture receipts and invoices

From uploaded documents the assistant extracts structured fields — supplier, date, net/gross, tax rate, line items — and proposes a pre-capture. Accountants check every value against the original document and approve; the AI takes over the typing, not the responsibility.

02

Review invoices for plausibility

The assistant flags conspicuous points (missing mandatory details, deviating amounts, unusual line items) as a prompt to check. The decision about approval, posting or payment stays strictly human — the AI does not replace a factual or tax review.

03

Turn reporting into readable text

From reviewed figures out of the accounting system, the assistant drafts understandable explanations and management summaries. It interprets and phrases — the figures themselves come from the audited system, not from the AI's own arithmetic.

04

Answer questions about posting and expense policies

An assistant connected to the internal policy handbook answers recurring questions (expenses, account assignment, deadlines) with a source reference — relieving accounting of routine questions and keeping answers traceable.

05

Build a finance assistant and bake in the review steps

Finance leadership assembles an assistant with its own policies and a fixed review reminder ('double-check every posting') without code and releases it to the team — so human control is part of the workflow, not optional.

Example

Input and result side by side

Input

Extract the posting-relevant fields from this uploaded incoming invoice: supplier, invoice number, invoice date, net amount, tax rate, tax amount, gross amount and the line items. Output the result as a table and clearly flag it if a legally mandatory detail (e.g. VAT ID or date of supply) is missing. Do not calculate anything yourself — only take over what is on the document.

Result

FieldDetected valueStatus
SupplierMuster GmbHtaken over — please check
Invoice number2026-0815taken over — please check
Invoice date14/06/2026taken over — please check
Net amount€1,000.00taken over — please check
Tax rate / amount19 % / €190.00taken over — please check
Gross amount€1,190.00taken over — please check
VAT ID—⚠ mandatory detail missing — clarify manually
Next step

Implement it in your company

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Security and selection

Financial data is among the most sensitive company data, so the finance assistant runs exclusively GDPR-compliantly: EU hosting, a data processing agreement (DPA) as standard, and input is not used to train the models. Access to documents, policies and data sources follows strict permissions; all access runs through central permission management with SSO and is traceable through audit logs — important for audit readiness and review. Financial data therefore stays under control inside the company instead of being processed through private AI accounts (shadow AI).

What to check when choosing a solution

  • Human control: Does the setup support a four-eyes principle in which every posting-relevant statement is reviewed?
  • Data protection: EU hosting, a DPA and no training on your input — for sensitive financial and personal data?
  • Source/document grounding: Are extracted data and statements output with a reference to the original document rather than invented?
  • Governance: Central permission management, audit logs and SSO for sensitive financial data?
  • Connections: Can permitted data sources (DMS, policies) be linked via connector/API — with permissions?
  • Adoption: Is there training and are there champions, so the team uses AI correctly and with review?
Known limitations

What needs to be clarified before rollout.

These points need to be clarified professionally or organisationally before rollout.

  1. 01

    Every posting-, tax- or payment-relevant statement must be reviewed and approved by a human — AI may pre-capture and flag, but must not post, approve or trigger payments on its own.

  2. 02

    AI models can misread or invent amounts, tax rates or fields; extracted values must always be checked against the original document, and a four-eyes principle is strongly recommended.

  3. 03

    The AI does not replace tax or legal advice; responsibility for correct account assignment, accounting treatment and compliance with GoBD and tax law stays with the company or its tax adviser.

  4. 04

    Financial and document data are sensitive and partly personal; they may only be processed through a GDPR-compliant, centrally managed platform and never through private AI accounts.

Frequently asked questions

No — AI may pre-capture receipts and invoices, extract data and flag issues, but the posting, approval and payment must always be reviewed and owned by a human. A four-eyes principle is recommended, as models can misread amounts or fields.

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