Training course – AI Agents – Legal

AI Agents for Legal Professionals

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

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

This course connects AI Agents with the everyday processes of Legal. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. In this compact course you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

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 how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • 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 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time
Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
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

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. 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. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

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 Tue, 15 December 2026 6 hrs Request
  • Salzburg Wed, 16 December 2026 6 hrs Request
  • Berlin Wed, 16 December 2026 6 hrs Request
  • Augsburg Wed, 16 December 2026 6 hrs Request
  • Hanover Mon, 14 December 2026 6 hrs Request
  • Bremen Wed, 16 December 2026 6 hrs Request
  • Stuttgart Fri, 11 December 2026 6 hrs Request
  • Kaiserslautern Mon, 14 December 2026 6 hrs Request
  • Online Tue, 15 December 2026 6 hrs Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

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 “AI Agents 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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