Training course – ChatGPT – IT Service Desk & Support

ChatGPT for IT Service Desk and Support Teams

Use ChatGPT safely and productively at work: projects, custom GPTs, data analysis, Canvas and privacy settings in team workspaces.

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

“ChatGPT for IT Service Desk and Support Teams” is designed for roles such as First- and second-line service desk analysts, Team leads and service desk managers and IT administrators and end-user support and shows step by step how to use ChatGPT productively, safely and transparently in IT Service Desk & Support – from the fundamentals to advanced workflows.

For many business teams, ChatGPT is the first AI tool they use every day – yet there is a methodical gap between asking the odd question and achieving real productivity gains. In this hands-on day you learn to apply ChatGPT deliberately to recurring work: drafting and editing text, summarising documents, analysing spreadsheets and structuring decision papers. You work with Projects that keep files and instructions together, with Canvas for reworking longer documents, and with data analysis for Excel and CSV files. Every exercise is based on genuine tasks from your own function.

The second focus is scale and responsibility. You build a custom GPT that knows your templates, tone of voice and review rules, and that colleagues across the workspace can use. We also clarify which data belongs in ChatGPT and which does not, how Team and Enterprise workspaces differ from personal accounts, and which settings matter for model training, memory and sharing. You leave with a personal prompt library, a working GPT and clear ground rules for using ChatGPT responsibly across 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 write structured prompts that reliably produce usable results for your day-to-day tasks.
  • You organise your work in Projects and revise longer documents efficiently with Canvas.
  • You analyse spreadsheets and files with data analysis and critically verify the results.
  • You build a custom GPT for a recurring task and share it with your team.
  • 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 Foundations and effective prompting
  • How language models work: strengths, limitations and hallucinations
  • Building effective prompts with role, context, task and output format
  • Refining iteratively instead of starting over: follow-ups and correction loops
  • Choosing models and using web search and deep research appropriately
Module 2 Projects, Canvas and document work
  • Setting up Projects to group files, instructions and chats by topic
  • Summarising, comparing and interrogating long documents
  • Using Canvas to revise text and drafts section by section
  • Templates for emails, reports, minutes and presentation outlines
Module 3 Data analysis with spreadsheets and files
  • Uploading, cleaning and analysing Excel and CSV files
  • Calculating KPIs, replicating pivot logic and explaining variances
  • Generating charts and preparing them for presentations
  • Verifying results: checking calculation steps and sanity checks
Module 4 Custom GPTs for recurring tasks
  • Identifying and scoping good use cases for GPTs
  • Configuring instructions, knowledge files and conversation starters
  • Testing, improving and sharing a GPT within the workspace
  • Maintenance, change tracking for instructions and ownership in the team
Module 5 Privacy, workspaces and governance
  • Personal accounts versus Team and Enterprise workspaces
  • Settings for model training, memory, temporary chats and sharing
  • Handling personal and confidential data in line with GDPR
  • Internal usage policy and quality assurance for AI output
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

Confident use of office applications and a web browser; no prior AI knowledge is required. Feel free to bring your own non-confidential sample tasks from your daily work. Experience in IT support or IT service management; basic scripting skills are helpful but not required.

Technical requirements

A laptop with an up-to-date browser and a ChatGPT account; a paid plan or access to your organisation's Team or Enterprise workspace is recommended for custom GPTs, Projects and data analysis.

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 Mon, 14 December 2026 6 hrs Request
  • Salzburg Wed, 16 December 2026 6 hrs Request
  • Berlin Wed, 16 December 2026 6 hrs Request
  • Augsburg Mon, 14 December 2026 6 hrs Request
  • Hanover Tue, 15 December 2026 6 hrs Request
  • Bremen Tue, 15 December 2026 6 hrs Request
  • Stuttgart Fri, 11 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 a paid ChatGPT licence for the course?

You can follow the fundamentals with a free account. However, features such as custom GPTs, Projects with larger files and advanced data analysis are tied to paid plans or come with far more generous limits there. Ideally you join with access to your organisation's Team or Enterprise workspace, so you practise under real conditions.

May I enter confidential company data into ChatGPT?

That depends on your plan, your contractual terms and your internal policy. In Team and Enterprise workspaces, content is not used for training by default, but GDPR and confidentiality obligations still apply. In the course you learn how to classify and anonymise data and how to choose the right settings.

How is a custom GPT different from a saved prompt?

A GPT bundles persistent instructions, knowledge files and optional tools such as web search or data analysis into a dedicated assistant. Colleagues can use it without any prompting skills and get consistent results. A saved prompt, by contrast, has to be copied and supplemented with context every time, which is far more error-prone.

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 “ChatGPT 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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