Training course · Generative AI · Leadership & Management

Generative AI for Leaders

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 Leaders” is designed for roles such as Managing directors and board members, Division and department heads and Team leaders and shows step by step how to use Generative AI productively, safely and transparently in Leadership & Management – from the fundamentals to advanced workflows.

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.

For leaders, generative AI matters in two ways: as a personal tool and as a strategic topic for the organisation. Personally, AI helps you grasp decision papers faster, structure strategy documents, prepare difficult conversations and sharpen your own communication. Strategically, leaders must judge where AI creates real value, what risks arise and how to support their teams in building skills. AI agents are changing roles, processes and responsibilities, which calls for clear guardrails, employee participation and an open learning culture. Leaders who have experienced AI hands-on can assess opportunities realistically, steer investment purposefully and lead change credibly.

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?

  • Managing directors and board members
  • Division and department heads
  • Team leaders
  • Strategy and transformation leads
  • Emerging leaders

Typical challenges we address

  • Information overload from reports, emails and decision papers
  • Uncertainty about where AI realistically adds value in your area
  • Teams with very different levels of AI knowledge and reservations
  • Legal, ethical and employee relations questions when introducing AI

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 confidently in your day-to-day leadership work for analysis, communication and preparation.
  • Assess AI opportunities and risks in your area realistically and prioritise pilot projects.
  • Lead AI adoption in your team with clear guardrails, participation and upskilling.

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: Leadership & Management
  • Condensing decision papers
  • Strategy sparring
  • Preparing one-to-ones
  • Leadership communication
  • Assessing AI potential
  • More effective meetings
Module 7 Data protection, quality & transfer to daily work
  • Introducing AI systems capable of monitoring employee behaviour or performance is subject to co-determination by works or staff councils where these exist, and employee data requires particular protection under the GDPR. The EU AI Act also requires organisations to ensure adequate AI literacy among staff and to scrutinise high-risk applications, for example in HR.
  • 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

Condensing decision papers

Lengthy reports, business cases and analyses are distilled into key messages, assumptions, risks and open questions so you can form a sound judgement faster and ask targeted follow-up questions.

Strategy sparring

AI acts as a critical sounding board for strategic options, runs through scenarios, formulates counter-arguments and helps surface assumptions and blind spots in plans. The decision remains yours.

Preparing one-to-ones

Guides for feedback, objective-setting or conflict conversations are structured, wording is refined and possible reactions are rehearsed – without entering personal details into unapproved tools.

Leadership communication

Announcements, speeches, change messages and answers to tough questions are drafted for the audience and adjusted in tone, clarity and length for staff, boards or customers.

Assessing AI potential

Together with the team, processes are systematically screened for AI suitability, prioritised by benefit and effort and translated into concrete pilot projects. Success criteria are defined up front.

More effective meetings

Agendas, pre-reads and minutes are prepared with AI, making meetings shorter and more decision-focused while actions are tracked clearly. Recurring formats can gradually be standardised as well.

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. Leadership or management responsibility, or preparation for such a role; no technical background required.

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

Introducing AI systems capable of monitoring employee behaviour or performance is subject to co-determination by works or staff councils where these exist, and employee data requires particular protection under the GDPR. The EU AI Act also requires organisations to ensure adequate AI literacy among staff and to scrutinise high-risk applications, for example in HR.

Suggested dates

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

  • Tue, 24 November 2026 Online Request
  • Thu, 3 December 2026 Kaiserslautern Request
  • Thu, 10 December 2026 Online Request
  • Fri, 18 December 2026 Bremen Request
  • Thu, 21 January 2027 Online Request
  • Tue, 2 February 2027 Salzburg 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.

Why should leaders use AI hands-on themselves?

Only those who have tried AI tools themselves can judge benefits, limits and effort realistically, steer investment sensibly and support their teams credibly. The course therefore combines practical exercises on your own leadership tasks with strategic questions about organisational adoption.

What about works councils and employee representatives?

Where AI systems can be used to monitor employee behaviour or performance, employee representatives usually have co-determination rights. Early involvement, transparent objectives and a framework agreement on AI use have proven effective. In the course we discuss typical provisions and steps towards a trust-based rollout.

How much does “Generative AI for Leaders” 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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