Training course · Prompt Engineering · Compliance & Data Protection

Prompt Engineering for Compliance and Data Protection Teams

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

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

“Prompt Engineering for Compliance and Data Protection Teams” is a hands-on course for roles such as Compliance officers and managers, Data protection officers and privacy coordinators and Information security officers. Rather than learning Prompt Engineering in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Compliance & Data Protection.

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.

Compliance and data protection teams must keep track of a growing body of rules, from the GDPR and whistleblower protection to supply chain due diligence and the EU AI Act. Generative AI can structure and accelerate this work: AI assistants summarise new regulations, produce gap analyses against existing policies, support records of processing activities and data protection impact assessments and draft clear training content. Automation helps with data subject requests, contract reviews and vendor risk assessments. At the same time, compliance teams are expected to steer AI use across the organisation: AI policies, risk classification under the AI Act and staff AI literacy obligations. Teams that use AI confidently themselves can advise the business better and design effective governance.

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?

  • Compliance officers and managers
  • Data protection officers and privacy coordinators
  • Information security officers
  • Governance, risk and compliance staff
  • AI governance leads

Typical challenges we address

  • Tracking numerous new regulations and translating them into internal requirements
  • Keeping records of processing and impact assessments up to date
  • Advising business units quickly and soundly when they introduce new tools
  • Steering organisation-wide AI use in a compliant way

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 regulatory analysis, data protection documentation and contract reviews.
  • Build AI governance with a policy, a tool inventory and risk classification.
  • Advise business units soundly on GDPR and AI Act requirements for AI use.

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: Compliance & Data Protection
  • Regulatory gap analysis
  • Records of processing and DPIAs
  • Reviewing data processing agreements
  • Data subject requests
  • Building AI governance
  • Training and awareness
Module 7 Data protection, quality & transfer to daily work
  • Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.
  • 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

Regulatory gap analysis

An AI assistant summarises new regulations, compares requirements with existing policies and processes and produces a structured list of gaps and actions for expert assessment.

Records of processing and DPIAs

Process descriptions and interviews are turned into draft entries for the record of processing activities and risk analyses for data protection impact assessments, reviewed by the DPO.

Reviewing data processing agreements

AI checks vendors' data processing agreements and privacy documentation for the mandatory content under Article 28 GDPR, third-country transfers and technical measures and flags deviations from the internal standard.

Data subject requests

Automations log access and erasure requests, monitor deadlines and draft responses, while data searches and final approval remain with the responsible staff.

Building AI governance

AI helps draft AI policies, build an inventory of AI systems in use and classify them according to the EU AI Act risk categories as a basis for governance board decisions.

Training and awareness

Policies are turned into clear learning modules, case studies and quizzes on data protection, anti-money laundering, anti-corruption or AI literacy, tailored to target groups across the organisation.

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 compliance, data protection or information security and are familiar with the basics of the GDPR.

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

Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.

Suggested dates

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

  • Mon, 23 November 2026 Online Request
  • Fri, 4 December 2026 Munich Request
  • Thu, 10 December 2026 Online Request
  • Wed, 13 January 2027 Hanover Request
  • Tue, 26 January 2027 Online Request
  • Fri, 12 February 2027 Berlin 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.

What does the EU AI Act actually require of companies?

Since early 2025, certain AI practices have been prohibited and organisations must ensure AI literacy among staff. Further obligations cover transparency and providers and deployers of high-risk systems. In the course we classify typical use cases and work out which governance components your organisation needs.

Can data protection officers use AI themselves?

Yes, for example for contract reviews, draft documentation or training content, provided no unnecessary personal data is processed. The legal assessment remains with you. Hands-on experience with AI also improves your advice to the business, because you can judge opportunities and risks more realistically.

How much does “Prompt Engineering for Compliance and Data Protection 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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