Training course – Generative AI – Legal

Generative AI for Legal Professionals

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

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

“Generative AI for Legal Professionals” is a hands-on course for roles such as Lawyers and partners in law firms, In-house counsel and corporate lawyers and Paralegals and legal assistants. Rather than learning Generative AI in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Legal.

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.

Legal departments and law firms work with large volumes of text: contracts, pleadings, statutes, judgments and correspondence. That is why generative AI is changing legal work so profoundly. AI assistants summarise case files and judgments, draft contracts from model clauses, compare contract versions, identify risks in clauses and prepare outlines for submissions. AI agents and automation support due diligence reviews, deadline management and answering recurring questions from the business. Diligence remains essential: language models can invent citations or misstate the law, and client confidentiality and professional rules set clear limits on data processing. Lawyers who combine AI with verified sources, clear review steps and secure environments gain time for strategy, negotiation and advice.

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?

  • Lawyers and partners in law firms
  • In-house counsel and corporate lawyers
  • Paralegals and legal assistants
  • Legal operations and legal tech leads
  • Contract managers

Typical challenges we address

  • Reviewing large numbers of contracts and files in a short time
  • Ensuring consistent quality for standard contracts and recurring requests
  • Keeping track of case law and legislative changes efficiently
  • Protecting client and business secrets when using digital tools

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 for contract review, drafting and file summaries with systematic source verification.
  • Automate recurring legal workflows such as standard contracts and requests from the business.
  • Use AI while upholding client confidentiality, professional rules and the GDPR.

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: Legal
  • Contract review
  • Contract drafting
  • Summarising files and judgments
  • Due diligence support
  • Structuring submissions
  • Legal self-service for the business
Module 7 Data protection, quality & transfer to daily work
  • Lawyers are bound by professional secrecy, in Germany under the Federal Lawyers' Act and Section 203 of the Criminal Code; client data may only be shared with service providers bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be anonymised, and AI output must always be checked against primary sources.
  • 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

Contract review

An AI assistant checks contracts against an internal playbook, flags deviating or missing clauses such as limitation of liability, jurisdiction or termination rights and suggests alternative wording for lawyers to evaluate.

Contract drafting

Approved model clauses and a structured questionnaire produce a draft contract, for example a non-disclosure or services agreement, including explanations for the business team.

Summarising files and judgments

AI condenses extensive files, submissions or judgments into facts, issues, arguments and outcome and creates chronologies that are checked against the originals.

Due diligence support

Contracts in data rooms are searched for change-of-control clauses, exclusivities, terms or liability risks, and findings are prepared in an overview for the due diligence report.

Structuring submissions

AI proposes outlines and lines of argument for submissions, opinions or memos, drafts individual sections and checks texts for contradictions and clarity.

Legal self-service for the business

A knowledge assistant answers standard questions from business units, such as contract approval or signing authority, based on internal policies and routes complex requests to the legal team.

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 a legal role, for example at a law firm or in-house legal department, and regularly handle contracts or submissions.

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

Lawyers are bound by professional secrecy, in Germany under the Federal Lawyers' Act and Section 203 of the Criminal Code; client data may only be shared with service providers bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be anonymised, and AI output must always be checked against primary sources.

Dates & locations

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

  • Munich Fri, 11 December 2026 6 hrs Request
  • Salzburg Tue, 15 December 2026 6 hrs Request
  • Berlin Thu, 10 December 2026 6 hrs Request
  • Augsburg Thu, 10 December 2026 6 hrs Request
  • Hanover Mon, 14 December 2026 6 hrs Request
  • Bremen Mon, 14 December 2026 6 hrs Request
  • Stuttgart Tue, 15 December 2026 6 hrs Request
  • Kaiserslautern Mon, 14 December 2026 6 hrs Request
  • Online Thu, 10 December 2026 6 hrs 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 lawyers enter client data into AI tools?

Only if the provider has been carefully selected, is bound to confidentiality, is contractually integrated under data protection law and does not use inputs for training. Otherwise, work with anonymised facts. In the course we develop clear, practical guidelines for this.

How do we deal with invented citations?

Language models can invent case numbers, sections or quotes. Use AI with supplied sources as context or with legal databases that provide verified references, and check every citation before using it. We practise this review routine in the course with realistic examples.

How much does “Generative AI for Legal Professionals” 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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