Training course – AI Agents – IT Service Desk & Support

AI Agents for IT Service Desk and Support Teams

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

“AI Agents for IT Service Desk and Support Teams” is a hands-on course for roles such as First- and second-line service desk analysts, Team leads and service desk managers and IT administrators and end-user support. Rather than learning AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from IT Service Desk & Support.

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.

The IT service desk is the first point of contact for incidents, requests and questions about devices, software and access. Rising ticket volumes, more complex IT estates and hybrid working put support teams under growing pressure. Generative AI and AI agents are changing this field particularly strongly: they classify and prioritise tickets, suggest fixes from the knowledge base, write clear replies for users, turn resolved cases into knowledge articles and answer standard requests through self-service around the clock. Scripts for recurring admin tasks can also be produced faster with AI. That leaves specialists more time for complex incidents, problem management and service improvement.

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?

  • First- and second-line service desk analysts
  • Team leads and service desk managers
  • IT administrators and end-user support
  • IT service management and knowledge management leads
  • Internal and external support providers

Typical challenges we address

  • High ticket volumes with many repetitive requests
  • Incomplete or outdated knowledge bases
  • Users with very different levels of IT literacy
  • Meeting service levels with limited resources

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.
  • Handle tickets faster, more consistently and more user-friendly with AI support.
  • Build an up-to-date, well-structured knowledge base with AI.
  • Design self-service and automation solutions with a sensible handover to people.

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: IT Service Desk & Support
  • Classifying and prioritising tickets
  • Fix suggestions from knowledge
  • Clear user communication
  • Writing knowledge articles
  • Self-service and chatbots
  • Scripts for routine tasks
Module 7 Data protection, quality & transfer to daily work
  • Tickets often contain personal data, access details and information about IT infrastructure that must not flow into unapproved AI services; passwords and keys never belong in prompts. Using ticket data to evaluate staff performance requires compliance with the GDPR and employee representation rules, and AI-generated scripts must be reviewed according to IT security policies.
  • 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

Classifying and prioritising tickets

Incoming tickets are categorised by type, urgency and affected service, missing information is detected and follow-up questions to users are prepared automatically. Duplicate tickets and related incidents are detected too.

Fix suggestions from knowledge

Drawing on the knowledge base, past tickets and vendor documentation, AI suggests resolution steps, which the analyst checks and adapts to the specific situation. Sources are always cited.

Clear user communication

Technical fixes are turned into clear, friendly step-by-step guides, incident status updates are drafted and replies are provided in several languages. Fewer follow-up questions arise, and users can solve simple issues themselves.

Writing knowledge articles

Resolved tickets and notes become structured knowledge articles with symptom, cause and resolution; outdated articles are identified and flagged for review. Team knowledge keeps growing and stays current.

Self-service and chatbots

AI agents answer standard questions such as password resets, VPN setup or printer issues in the self-service portal and hand complex cases to the team with a summary.

Scripts for routine tasks

Administrators use AI to create PowerShell or Bash scripts for recurring tasks such as user provisioning or reports, and test them carefully before use. A review before production use is mandatory.

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 IT support or IT service management; basic scripting skills are helpful but not 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

Tickets often contain personal data, access details and information about IT infrastructure that must not flow into unapproved AI services; passwords and keys never belong in prompts. Using ticket data to evaluate staff performance requires compliance with the GDPR and employee representation rules, and AI-generated scripts must be reviewed according to IT security policies.

Dates & locations

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

  • Munich Wed, 16 December 2026 6 hrs Request
  • Salzburg Tue, 15 December 2026 6 hrs Request
  • Berlin Mon, 14 December 2026 6 hrs Request
  • Augsburg Tue, 15 December 2026 6 hrs Request
  • Hanover Tue, 15 December 2026 6 hrs Request
  • Bremen Thu, 10 December 2026 6 hrs Request
  • Stuttgart Thu, 10 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 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.

Will an AI chatbot replace first-line support?

An AI agent can resolve many standard requests on its own and pre-qualify tickets. Complex incidents, exceptions and users who need personal help stay with the team. Success depends on a clear handover with a summary. In the course you design such handovers and define which cases are suitable for automation.

How do I prevent incorrect fix suggestions from AI?

Ground the AI in verified knowledge such as your knowledge base and vendor documentation, ask for sources and check critical steps before executing them. For changes to systems, the four-eyes principle applies. The course shows how to build quality assurance into the support process.

How much does “AI Agents for IT Service Desk and Support Teams” 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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