Business fields · IT Service Desk & Support

AI training for IT Service Desk and Support Teams

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.

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  • Incomplete or outdated knowledge bases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

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Resolved tickets and notes become structured knowledge articles with symptom, cause and resolution; outdated articles are identified and flagged for review.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

Possible hands-on projects

Ticket triage tool

A small web app that reads ticket exports, groups requests by topic and highlights frequent problem areas as candidates for self-service solutions.

Knowledge article editor

An internal tool that generates a draft article from ticket notes using a fixed template and manages the article's approval status.

Onboarding checklist

An app that generates a role-based checklist of access rights, devices and software for new starters and tracks progress. Offboarding works the same way.

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.

Prerequisites

Experience in IT support or IT service management; basic scripting skills are helpful but not required.

Frequently asked questions

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.

Request without obligation

We will get back to you within one working day with a confirmation or an alternative suggestion.

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Total €949 plus VAT