Training course · AI Agents · Education & Teaching

AI Agents for Educators

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

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents for Educators” is designed for roles such as Teachers in general and vocational schools, University lecturers and Trainers in adult and continuing education and shows step by step how to use AI Agents productively, safely and transparently in Education & Teaching – from the fundamentals to advanced workflows.

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. Over two days 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.

Schools, universities, adult education providers and corporate academies are undergoing a fundamental shift with generative AI. Educators use AI assistants to differentiate teaching materials, create tasks at different levels, prepare feedback and write course descriptions. At the same time, AI challenges established assessment formats, coursework and the very notion of independent work. Educational institutions therefore have two jobs: to make their own work lighter in sensible ways and to equip learners to use AI competently and critically. A pedagogically sound approach frees up time for individual support, while careless use risks lower quality, data protection issues and unclear grading criteria.

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?

  • Teachers in general and vocational schools
  • University lecturers
  • Trainers in adult and continuing education
  • L&D and corporate academy managers
  • Heads of school and programme directors

Typical challenges we address

  • Mixed-ability groups that need differentiated materials
  • Heavy workload for marking, feedback and documentation
  • Uncertainty about assessment and independent work in the age of AI
  • Unclear rules on which tools may be used with which data

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.
  • Create differentiated teaching and learning materials with AI while safeguarding subject accuracy.
  • Develop assessment and task formats that deal sensibly with AI use.
  • Draft practical rules for privacy-compliant AI use in your institution.

Course outline

Day 1

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

Day 2

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: Education & Teaching
  • Differentiating materials
  • Generating tasks and exercises
  • Preparing feedback
  • Course and module planning
  • Building learners' AI literacy
  • Communication and administration
Module 7 Data protection, quality & transfer to daily work
  • Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.
  • 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

Differentiating materials

From a source text, AI creates versions for different ability levels, language proficiency or support needs – with glossaries, guiding questions and extension tasks that the teacher checks and adapts.

Generating tasks and exercises

Practice questions, case studies, quizzes and model answers are created to match learning objectives and competence levels and can be imported into learning platforms. Variants for resits are easy to produce too.

Preparing feedback

Based on a marking rubric, AI drafts constructive, criteria-based feedback on anonymised work, which the educator adds to, weighs and takes responsibility for. Learners receive detailed feedback sooner.

Course and module planning

AI supports outline and lesson planning for teaching units, seminars or trainings, suggests changes of method and drafts module descriptions with clear learning outcomes. Timings and material lists are included.

Building learners' AI literacy

Educators design tasks in which learners use AI deliberately, verify its output and reflect on their process, rather than simply banning or ignoring AI use.

Communication and administration

Letters to parents, participant information, meeting minutes and FAQ answers are drafted faster, prepared in several languages and brought into a consistent tone. Key dates and deadlines are highlighted.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Experience in teaching, training or education management; no technical background required.

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

Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 – Fri, 4 December 2026 Hanover Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Munich Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Online Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Stuttgart 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.

Can I let AI mark my students' work?

AI can prepare feedback drafts on anonymised texts, but grading remains your responsibility. Names, marks and support information do not belong in unapproved tools. In the course we practise anonymising work, applying rubrics and critically weighing AI suggestions. Responsibility stays clearly with you.

How should I deal with AI-written coursework?

Bans alone fall short, and AI detectors are unreliable. More effective are formats that make process and reflection visible, such as oral components, learning journals or disclosed AI use. The course presents concrete task formats and policies that allow independent work to be assessed fairly.

How much does “AI Agents for Educators” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 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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