Receipts, invoices, payment lists, and reports are part of everyday life at any company. Many of these tasks are repetitive: searching for information, naming documents, transferring data, drafting follow-up questions, and preparing documents for tax advisors or the accounting department.
Generative AI therefore has significant potential right before the actual booking takes place. It can explain, extract, and structure information, and flag potential anomalies. However, the booking, legal review, and approval remain the responsibility of qualified professionals.
AI doesn't replace accounting—it improves the preparation
The workshop was deliberately designed as a hands-on introduction. Instead of focusing on a single tool, we looked at an end-to-end process:
Understand → Extract → Verify → Organize → Transfer
This pattern can be applied to many business tasks. It is important to clearly separate the individual steps from one another. A number extracted automatically is not yet a verified number. An indication of an anomaly is not yet a tax or legal assessment.
1. Explain balance sheets in a way that's easy to understand
Balance sheet statements contain a wealth of information, but they are not easy for everyone to read. An AI assistant can help explain line items in plain language, highlight changes from one period to the next, and prepare questions for further professional review.
Please note: This explanation is intended as a guide only. It does not replace account assignment, financial statement preparation, or interpretation by an accounting or tax advisor.
2. Read Incoming Invoices in a Structured Manner
For example, information such as the supplier, date, description of services, net and gross amounts, and payment terms can be extracted from invoices. Instead of manually typing in this information, it can be prepared in a structured format for a subsequent process.
The benefits are particularly evident in recurring processes: naming documents consistently, pre-filling fields, flagging missing information, and then transferring the documents to the existing accounting or ERP system.
3. Check invoices for irregularities
Generative AI can serve as an additional verification tool to flag missing or contradictory information. For example, it can generate questions when totals appear unclear, required fields are missing, or information does not match.
However, a language model is not a reliable source of verification and can itself generate errors. Therefore, suggestions must be verifiable and reviewed by an expert.
4. Organize Bank and Cash Flows
Even anonymized payment lists can be grouped according to clear criteria: recurring payees, unusual descriptions, missing assignments, or possible categories. This can make it easier to prepare for a reconciliation and help identify outstanding issues more quickly.
When it comes to actual banking and payment data, security requirements and access permissions are particularly stringent. Sensitive data should only be stored in a technical and contractual environment that has been approved for that purpose.
5. Pre-fill systems in a controlled manner
The next step after the analysis is to transfer the data to existing applications. An AI-powered process can convert information into a predefined format or pre-fill defined fields in a web application.
Productive automation requires clear boundaries: separate test environments, minimal permissions, logging, and human approval before binding reservations or payments are made.
Better Collaboration with Tax Advisors
One often underestimated benefit is the structured handoff. AI can compile open items, missing documents, and prepared follow-up questions into a single, standardized list. It can also generate monthly closing checklists or clear summaries based on approved data.
This does not automate the technical work involved in tax consulting. Rather, it improves the quality of preparation—and both parties spend less time searching for information, requesting additional data, and re-entering data.
Consider Data Privacy and Data Quality from the Very Beginning
Invoices, IBANs, personal data, and account transactions may contain sensitive personal or business information. Such data must not be uploaded to any public AI services without proper oversight.
Before implementation, the following must be clarified, among other things: purpose, legal basis, data minimization, storage location, data processing on behalf of a third party, roles, retention periods, and technical safeguards. A contract or business license alone does not automatically make a process compliant with data protection regulations.
Conclusion: The greatest leverage often lies in the pre-booking stage
The two demonstrations at Haindorf Castle showed just how broad the range of applications already is. Generative AI can make accounting tasks easier to understand, organize documents, and highlight open questions more quickly.
The responsible approach begins with a clearly defined process, anonymized test data, and someone who can evaluate the results from a technical perspective. This way, AI becomes a useful assistant—not an uncontrolled black box.
Workshop Recap · May 5 and June 1, 2026
Accounting & More with AI: Hands-On Workshops at Haindorf Castle
On May 5, 2026, and again on June 1, 2026, I led the hands-on workshop “Accounting & More with AI Tools” for the House of Digitalization at Haindorf Castle in Langenlois. The workshop focused on how generative AI can support accountants and finance teams in their preparatory work—without delegating professional responsibility to a model.