Training course · Generative AI · Recruiting

Generative AI for Recruiters

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 Recruiting. 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.

With talent shortages in many fields, recruiting has become a key business function: candidates must be found, convinced and guided quickly through the process. Generative AI supports recruiters at many points of the candidate journey. AI assistants write job ads that speak to the target group, build search strings for active sourcing, draft personal outreach messages, prepare structured interview guides and summarise interview notes. Automation handles scheduling, acknowledgements and status updates for applicants. At the same time, recruiting is a particularly sensitive area: selection decisions must be non-discriminatory and transparent, and AI systems used to screen candidates face strict requirements. Using AI for communication, structure and efficiency while keeping selection in human hands improves both candidate experience and time to hire.

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?

  • Recruiters and talent acquisition managers
  • Sourcers
  • HR generalists with recruiting responsibility
  • Employer branding leads
  • Recruitment consultants and staffing agencies

Typical challenges we address

  • Finding and approaching suitable candidates in tight labour markets
  • Writing job ads that genuinely reach the target group
  • Running fast application processes with a good candidate experience
  • Making fair, structured and legally sound selection decisions

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 targeted job ads, sourcing strategies and outreach messages with AI.
  • Structure selection processes with AI-supported guides and improve the candidate experience.
  • Use AI in recruiting in line with anti-discrimination law, the GDPR and the EU AI Act.

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: Recruiting
  • Job ad optimisation
  • Active sourcing strategies
  • Personal outreach
  • Structured interview guides
  • Candidate communication
  • Recruiting metrics analysis
Module 7 Data protection, quality & transfer to daily work
  • Selection processes must comply with anti-discrimination law such as the German General Equal Treatment Act (AGG); AI must not disadvantage people based on age, gender or origin. Applicant data is protected by the GDPR, solely automated rejections are not permitted under Article 22 GDPR, and AI systems for screening and selecting candidates are 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

Job ad optimisation

An AI assistant turns the role profile and team information into an inclusive job ad tailored to the target group, checks it for gender-neutral language and unnecessary barriers and creates variants for different channels.

Active sourcing strategies

AI builds Boolean search strings, alternative job titles and relevant skills for professional networks and job boards and suggests target companies and communities for direct approach.

Personal outreach

Based on the public profile and the role, AI drafts individual contact messages and follow-ups that make the specific value of the position clear to the person.

Structured interview guides

AI creates competency-based interview questions, rating anchors and case exercises for a role, so that all candidates are assessed against the same criteria.

Candidate communication

Automations send acknowledgements, scheduling proposals and status updates, while AI drafts respectful rejections and offers that recruiters review before sending.

Recruiting metrics analysis

Applicant tracking system exports are analysed for time to hire, channel performance and drop-off rates, bottlenecks identified and improvements proposed.

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 recruiting or talent acquisition and know your organisation's hiring process.

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

Selection processes must comply with anti-discrimination law such as the German General Equal Treatment Act (AGG); AI must not disadvantage people based on age, gender or origin. Applicant data is protected by the GDPR, solely automated rejections are not permitted under Article 22 GDPR, and AI systems for screening and selecting candidates are high-risk under the EU AI Act.

Suggested dates

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

  • Fri, 27 November 2026 Online Request
  • Mon, 7 December 2026 Salzburg Request
  • Wed, 16 December 2026 Online Request
  • Mon, 11 January 2027 Bremen Request
  • Thu, 21 January 2027 Online Request
  • Tue, 2 February 2027 Augsburg 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.

May AI pre-screen applications?

Systems that filter or rank applications are classified as high-risk AI under the EU AI Act, with extensive obligations. The GDPR also prohibits solely automated rejections. The course therefore focuses on AI for communication, structure and preparation, while screening and decisions remain with people.

How do we avoid discrimination by AI?

Language models can reproduce biases from their training data, for example in job ad wording. Check outputs specifically for protected characteristics, use structured criteria and never enter sensitive data into AI tools. We practise concrete review questions that you can adopt in your process.

How much does “Generative AI for Recruiters” 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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