Training course – Prompt Engineering – Tax Advisory

Prompt Engineering for Tax Advisers

Vendor-neutral prompt engineering: roles, context, few-shot examples, prompt chains, prompt libraries and systematic quality checks.

Duration
6 hours, one session
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 Prompt Engineering with the everyday processes of Tax Advisory. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Whether you use ChatGPT, Claude, Copilot, Gemini or Le Chat, the quality of the output depends largely on how the task is framed. Prompt engineering is the skill of conveying goal, context, constraints and desired format to a language model so that it reliably produces usable results. In this vendor-neutral practical day you learn proven techniques that work across all mainstream AI assistants: defining roles and audiences, selecting relevant context, working with examples and breaking complex tasks down into traceable steps. You try out every technique directly on tasks from your own working day.

The second part focuses on repeatability and quality across the team. You develop prompt templates with placeholders, build multi-step prompt chains for analysis, writing and review processes, and set up a shared prompt library. You learn to evaluate output systematically – with review criteria, test cases and targeted self-checks by the model – and to avoid typical pitfalls such as hallucinations, ambiguity and missing context. By the end you have a structured approach that works regardless of the tool you use and continues to pay off as new models arrive.

Tax advisory firms are under pressure from staff shortages, rising client expectations and a constant stream of legislative changes, administrative guidance and court rulings. Used responsibly, generative AI can provide real relief. AI assistants summarise case law and tax authority guidance, structure facts from client documents, draft client newsletters and objection letters and answer routine questions in plain language. Automation supports document intake, deadline management and client communication. Professional judgement and liability remain with qualified tax advisers, but research and drafting become faster. The key prerequisite is safe handling of client data: professional secrecy, professional conduct rules and the GDPR determine which tools may be used and how.

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?

  • Tax advisers and practice owners
  • Tax assistants and tax technicians
  • Accountants working in tax practices
  • Payroll staff
  • Practice managers and digital transformation leads

Typical challenges we address

  • Tracking and interpreting legislative changes, official guidance and court rulings promptly
  • Requesting and structuring incomplete client records
  • Reducing the time spent on submissions, objections and client correspondence
  • Coping with deadlines and seasonal peaks with limited staff

What you will be able to do

  • You understand how language models process prompts and derive effective wording from this.
  • You structure prompts with role, context, task, constraints and output format.
  • You use few-shot examples and prompt chains for complex, multi-step tasks.
  • You create reusable templates and build a shared prompt library.
  • Use AI for research, summaries and draft submissions and verify results against primary sources.
  • Automate client communication and document processes in your practice.
  • Use AI while respecting professional secrecy, professional conduct rules and the GDPR.

Course outline

Module 1 How language models process prompts
  • Core principles of language models: probabilities, context window, limitations
  • Why wording, order and examples change the result
  • What causes hallucinations and how prompts reduce them
  • Differences and common ground between mainstream AI assistants
Module 2 Building blocks of an effective prompt
  • Defining role, audience, task, context and output format
  • Stating constraints, exclusions and quality criteria
  • Structured input with sections, delimiters and tags
  • Asking the model to raise questions instead of making assumptions
Module 3 Advanced techniques
  • Zero-shot, one-shot and few-shot: setting style and structure with examples
  • Requesting step-by-step reasoning for complex tasks
  • Prompt chains: separating research, drafting, review and revision
  • Using change of perspective, counter-arguments and model self-critique
Module 4 Templates and prompt libraries
  • Creating reusable templates with placeholders and variables
  • Storing persistent instructions in projects, custom assistants and agents
  • Building, naming, maintaining and sharing a team prompt library
  • Documenting templates: purpose, inputs, expected output, owner
Module 5 Quality assurance and responsible use
  • Defining review criteria and scoring rubrics for AI output
  • Setting up test cases and systematically comparing and improving prompts
  • Verifying facts, figures and sources; establishing the four-eyes principle
  • Data protection, confidential content and transparency under GDPR and the EU AI Act
Module 6 Practice lab: Tax Advisory
  • Summarising case law
  • Drafting objections and submissions
  • Client communication
  • Document checklists
  • Automated document intake
  • Knowledge management
Module 7 Data protection, quality & transfer to daily work
  • German tax advisers are bound by professional secrecy under the Tax Advisers Act and Section 203 of the Criminal Code; client data may only be shared with AI providers contractually bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be consistently anonymised.
  • 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

Summarising case law

An AI assistant summarises rulings, tax authority guidance or draft legislation, highlights key points and affected client groups and drafts internal technical updates that qualified advisers then check against the original source.

Drafting objections and submissions

Based on anonymised facts, AI produces a structured draft of an objection, a request to suspend enforcement or a reply to the tax office, including an outline of the arguments for further professional work.

Client communication

AI drafts clear client newsletters, explanations of tax assessments and reminders about missing documents, adapted for private clients, freelancers or businesses.

Document checklists

For income tax returns, annual financial statements or payroll queries, AI creates tailored checklists based on the client profile, reducing follow-up questions and repeated requests.

Automated document intake

An automation sorts incoming client documents, recognises document types, applies consistent file names and passes them to the practice software or flags missing information.

Knowledge management

Internal guidance notes, review templates and model wording are prepared and made searchable with AI support, so staff can access proven practice know-how more quickly.

Prerequisites

Some initial experience with at least one AI assistant such as ChatGPT, Claude, Copilot or Gemini is helpful; no technical background is required. You work in a tax practice or corporate tax department and have a basic grounding in tax law.

Technical requirements

A laptop with an up-to-date browser and access to at least one AI assistant, ideally the tool approved within your organisation.

Data protection & compliance

German tax advisers are bound by professional secrecy under the Tax Advisers Act and Section 203 of the Criminal Code; client data may only be shared with AI providers contractually bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be consistently anonymised.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Mon, 14 December 2026 6 hrs Request
  • Salzburg Mon, 14 December 2026 6 hrs Request
  • Berlin Tue, 15 December 2026 6 hrs Request
  • Augsburg Thu, 10 December 2026 6 hrs Request
  • Hanover Thu, 10 December 2026 6 hrs Request
  • Bremen Mon, 14 December 2026 6 hrs Request
  • Stuttgart Fri, 11 December 2026 6 hrs Request
  • Kaiserslautern Tue, 15 December 2026 6 hrs Request
  • Online Wed, 16 December 2026 6 hrs Request

Frequently asked questions

Do these techniques work with every AI assistant?

Yes, the course is deliberately vendor-neutral. The principles – a clear task, relevant context, examples, structured output and review steps – work equally well in ChatGPT, Claude, Copilot, Gemini, Le Chat and other tools. Where assistants differ in detail, for example with projects or custom assistants, we show the corresponding features in each.

Won't better models soon make prompt engineering obsolete?

Models are getting better at interpreting vague requests, but they still cannot know what you do not tell them: audience, quality standards, internal requirements or relevant background. Good prompts are therefore mainly good task descriptions. Templates, prompt chains and quality checks also keep their value for teams as new models arrive.

What is a prompt library and how do we maintain it as a team?

A prompt library is an organised collection of proven templates for recurring tasks, each with its purpose, required inputs, a sample result and an owner. It can live in a shared document, a wiki or directly in the AI tool's projects. In the course you set up a first library and agree simple rules for maintenance and approval.

May client data be entered into AI tools?

Only under strict conditions: the provider must be bound to confidentiality as a service provider, data processing must be contractually GDPR-compliant and inputs must not be used for training. Otherwise, work with anonymised facts. In the course we develop practical rules tailored to your practice.

Can AI give binding answers to tax questions?

No. AI assistants can be wrong about provisions, deadlines or case law and may not know the latest changes. They are useful for structuring, first drafts and research pointers. Professional judgement and liability stay with qualified advisers, who check every statement against legislation, commentaries and case law.

How much does “Prompt Engineering for Tax Advisers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you 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 and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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