Training course · Generative AI · Human Resources

Generative AI for HR 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

“Generative AI for HR Teams” is a hands-on course for roles such as HR business partners, HR officers and generalists and Learning and development specialists. Rather than learning Generative AI in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Human Resources.

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.

HR departments are service providers, advisers and change agents at once: they manage contracts and processes, support managers and drive topics such as people development and company culture. Generative AI can take a lot off their plate. AI assistants draft policies, employment references, job descriptions and employee communications, answer recurring questions on leave, working time or benefits and help design training and feedback processes. Automation speeds up onboarding and offboarding and analyses employee surveys. HR, however, demands particular care: personnel data is highly sensitive, decisions about people must remain fair and transparent, and many AI applications require works council involvement. Considering these conditions from the start builds acceptance and turns AI into genuine relief.

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?

  • HR business partners
  • HR officers and generalists
  • Learning and development specialists
  • Payroll and HR administration staff
  • Heads of HR and CHROs

Typical challenges we address

  • Handling recurring employee queries alongside strategic work
  • Producing policies, references and documents quickly and in a legally sound way
  • Coordinating onboarding and offboarding across many stakeholders
  • Analysing employee feedback and HR metrics meaningfully

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.
  • Create HR documents, communications and development concepts efficiently and soundly with AI.
  • Automate HR processes such as onboarding and employee queries with clear responsibilities.
  • Take employee data protection, co-determination and the EU AI Act into account when using AI in HR.

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: Human Resources
  • Drafting HR documents
  • Employment references
  • Employee self-service
  • Onboarding automation
  • Survey analysis
  • People development
Module 7 Data protection, quality & transfer to daily work
  • Personnel data is protected by the GDPR and national employee data protection rules; in Germany, introducing AI systems capable of monitoring behaviour or performance requires works council co-determination under the Works Constitution Act. AI used for decisions on promotion, termination or performance evaluation is high-risk under the EU AI Act.
  • 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

Drafting HR documents

An AI assistant drafts policies, works agreement proposals, job descriptions and employee information in plain language, which HR then checks against employment law and agrees internally.

Employment references

Based on a structured performance assessment, AI drafts a reference letter at the appropriate rating level with favourable yet truthful wording, which HR checks against established reference conventions.

Employee self-service

A knowledge assistant answers questions on leave, travel expenses, working time or benefits based on approved policies, cites the source and hands complex cases to HR.

Onboarding automation

Workflows create checklists, welcome emails, induction plans and tasks for IT, the line manager and buddies, so new joiners are well prepared from day one.

Survey analysis

Free-text answers from employee surveys or exit interviews are anonymised and clustered by theme, sentiment summarised and fields of action for leadership and HR derived.

People development

AI supports the design of training programmes, competency models, learning paths and guides for performance and feedback conversations, tailored to roles and company culture.

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 work in HR and know the core HR processes and basic employment law in your organisation.

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

Personnel data is protected by the GDPR and national employee data protection rules; in Germany, introducing AI systems capable of monitoring behaviour or performance requires works council co-determination under the Works Constitution Act. AI used for decisions on promotion, termination or performance evaluation is high-risk under the EU AI Act.

Suggested dates

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

  • Tue, 24 November 2026 Online Request
  • Tue, 1 December 2026 Munich Request
  • Thu, 10 December 2026 Online Request
  • Thu, 17 December 2026 Stuttgart Request
  • Wed, 13 January 2027 Online Request
  • Fri, 29 January 2027 Berlin 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.

Does the works council have to agree to AI use?

Often, yes. In Germany, as soon as an AI system is technically capable of monitoring employee behaviour or performance, the works council has co-determination rights, plus information and consultation rights. We show how to involve employee representatives early and what an AI framework agreement typically covers.

May we process personnel data in AI tools?

Only in approved environments with a data processing agreement, a clear purpose and a legal basis. Many tasks, such as drafting policies or training concepts, need no personal data at all. Where they do, minimise and pseudonymise the data. In the course we develop practical rules for your HR team.

How much does “Generative AI for HR 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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