Training course · Generative AI · Accounting

Generative AI for Accounting Teams

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Generative AI with the everyday processes of Accounting. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Generative AI has reached most organisations, yet teams often lack a shared understanding of what language models can actually do and where their limits lie. In this vendor-neutral course you will learn how large language models generate text, why they hallucinate and how careful prompting, context and source checking lead to reliable results. Rather than relying on any provider's marketing claims, you will work with transparent criteria that help you compare tools and judge their fit for your own tasks.

The second focus is everyday implementation. You will identify concrete use cases in your area of work, weigh benefit, risk and effort, and draft a realistic roll-out plan for your team. This covers ground rules for handling confidential data, a practical prompt library and ways to build acceptance and make results measurable. Throughout the day you work with examples from your own field, so you leave with an actionable roadmap rather than a set of abstract ideas.

Accounting is shaped by recurring processes, high document volumes and strict requirements for proper bookkeeping. Generative AI and automation provide real relief: AI assistants extract data from supplier invoices, suggest account assignments, explain transactions under local GAAP or IFRS and draft queries to suppliers or internal departments. AI agents support account reconciliations, the month-end close and the preparation of documents for external auditors and tax advisers. Responsibility for correct postings stays with people, but routine work shrinks, leaving time for exceptions, process improvement and analysis. The prerequisites are clear review steps, documented procedures and tools that respect requirements for traceability and immutability, such as the German GoBD principles.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • General ledger and accounts payable accountants
  • Accounts receivable specialists
  • Financial accountants preparing statements
  • Heads of accounting
  • Shared service centre staff

Typical challenges we address

  • Processing high volumes of documents in many formats on time
  • Resolving reconciliations and open items during the month-end close
  • Accounting correctly for complex transactions under GAAP, IFRS and VAT rules
  • Providing complete, traceable records for audits and tax inspections

What you will be able to do

  • You can explain clearly how language models generate text and why hallucinations occur.
  • You can write prompts that consistently deliver useful, verifiable results.
  • You can compare AI tools against transparent criteria covering data protection, features and cost.
  • You can identify and prioritise concrete use cases for your area of work.
  • Use AI for document processing, account assignment suggestions and reconciliations with clear review steps.
  • Use AI assistants to clarify GAAP, IFRS and VAT questions and verify the answers professionally.
  • Design AI-supported processes that meet bookkeeping compliance requirements and are fully documented.

Course outline

Module 1 How large language models work
  • Tokens, context windows and probabilities: what happens when a model generates text
  • Training knowledge versus web search versus your own documents (RAG)
  • Text, images, audio and code: what multimodal models can do today
  • Realistically assessing typical strengths and weaknesses in office work
Module 2 Spotting hallucinations and getting reliable output
  • Why models produce plausible-sounding errors and when the risk increases
  • Prompting techniques: role, context, examples, output format and step-by-step instructions
  • Requesting sources, cross-checking facts and introducing a four-eyes principle
  • Scoping tasks so that AI assists rather than decides
Module 3 Choosing tools without vendor bias
  • Overview of chat assistants, AI built into office suites and specialist tools
  • Criteria: data processing, hosting location, admin features, integrations and pricing model
  • Enterprise licences, API access and locally hosted open-source models compared
  • Building a simple scoring matrix for your own tool selection
Module 4 Identifying use cases in your field
  • Systematically capturing recurring writing, research and analysis tasks
  • Rating benefit, risk and implementation effort for each use case
  • Distinguishing quick wins from strategic initiatives
  • Creating a prioritised use-case backlog for your team
Module 5 Rolling out generative AI in your team
  • Usage rules: which data may go into which tool and who signs off results
  • Building and maintaining a shared prompt library and templates
  • AI champions, training formats and peer exchanges to embed new habits
  • Measuring success: documenting time saved, quality and user satisfaction
Module 6 Practice lab: Accounting
  • Invoice data extraction
  • Account assignment and guidance
  • Reconciliation support
  • Dunning and supplier communication
  • Close checklists and procedures
  • Audit request preparation
Module 7 Data protection, quality & transfer to daily work
  • AI-supported accounting processes must meet bookkeeping requirements such as the German GoBD, in particular traceability, immutability and up-to-date procedural documentation. Invoices and bank data contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Invoice data extraction

AI reads incoming invoices in PDF or e-invoicing formats, checks mandatory VAT details, suggests supplier, GL account and cost centre and flags incomplete or unusual documents for review.

Account assignment and guidance

An AI assistant explains transactions such as prepayments, provisions or capitalisation of assets, proposes possible journal entries and points to the relevant rules, which you then verify professionally.

Reconciliation support

Automations compare bank transactions with receivables and payables, match payments to open items and produce a list of unexplained differences with suggested explanations for the month-end close.

Dunning and supplier communication

AI drafts polite, factual payment reminders, queries about missing purchase order numbers or credit note requests and adapts tone and language for domestic and international customers and suppliers.

Close checklists and procedures

From existing notes, AI creates structured closing checklists, work instructions and sections of the procedural documentation required for compliant bookkeeping, which the team reviews and maintains.

Audit request preparation

When auditors or tax inspectors send requests, AI helps structure the questions, map the evidence required and draft clear explanations of postings, estimates and judgements.

Prerequisites

No technical background is required. It helps to bring along typical tasks from your day-to-day work that you would like to support with AI. You have a basic knowledge of financial accounting and work regularly with an ERP or accounting system.

Technical requirements

You will need a laptop with an up-to-date browser and internet access. A free account with a common AI assistant is sufficient; company licences are welcome.

Data protection & compliance

AI-supported accounting processes must meet bookkeeping requirements such as the German GoBD, in particular traceability, immutability and up-to-date procedural documentation. Invoices and bank data contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 Online Request
  • Wed, 2 December 2026 Augsburg Request
  • Mon, 14 December 2026 Online Request
  • Mon, 11 January 2027 Online Request
  • Wed, 27 January 2027 Kaiserslautern Request
  • Tue, 9 February 2027 Online Request

Frequently asked questions

Is the course tied to a specific AI tool?

No. The training is deliberately vendor-neutral. You work with widely used chat assistants and learn principles that apply to all major language models. That way you can transfer your skills to whichever tool your organisation has approved and evaluate new offerings yourself using clear criteria instead of relying on marketing statements.

How is confidential company data handled during the course?

For the exercises you use anonymised or fictitious examples from your area of work. At the same time you learn which categories of data may be entered into which tools, what to look for regarding data processing agreements and use of inputs for training, and how to set out these rules clearly for your team.

Will we leave with something concrete to implement?

Yes. You leave with a prioritised use-case backlog, a scoring matrix for tool selection, tested prompt templates and a draft set of team usage rules. These materials are designed so you can take them straight into internal discussions with management, IT and your data protection officer.

Are AI-supported postings compliant?

AI provides suggestions, but postings are made in your compliant accounting system after review by staff. What matters are documented review steps, logging and updated procedural documentation. In the course we work out how to embed AI steps cleanly in your process and make them transparent to auditors.

How well does AI handle invoices with different layouts?

Modern models usually process varied layouts and structured e-invoices reliably, but they make mistakes with blurred scans or unusual formats. Plausibility checks such as total reconciliation, VAT rate validation and supplier master data matching are therefore essential. We show how to build these controls into your workflow.

How much does “Generative AI for Accounting Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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