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AI exposure report
Will AI replace Computer User Support Specialists?
Many of your tasks are within reach of AI. The role will change, so it pays to act now.
Task exposure to today's AI
High exposure
This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.
Get your personal scoreWill AI replace Computer User Support Specialists?
Not entirely. Today's AI tools can take on about 58% of the typical work in this occupation, mostly: maintain records of daily data communication transactions, problems and remedial actions taken, or installation activities. The parts that stay human include: Set up equipment for employee use, performing or ensuring proper installation of cables, operating systems, or appropriate software.; Install and perform minor repairs to hardware, software, or peripheral equipment, following design or installation specifications.; Answer user inquiries regarding computer software or hardware operation to resolve problems..
People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.
Which tasks AI can take on
The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.
+ 10 more tasks (25% of the week) in the full test.
Your human edge
- Set up equipment for employee use, performing or ensuring proper installation of cables, operating systems, or appropriate software.
- Install and perform minor repairs to hardware, software, or peripheral equipment, following design or installation specifications.
- Answer user inquiries regarding computer software or hardware operation to resolve problems.
AI tools to try
Coding assistants (GitHub Copilot, Claude Code, Cursor)ChatGPT / Claude for design and debuggingAI test and documentation generatorsRelated roles
- Software Developers
- Computer Network Support Specialists
- Network and Computer Systems Administrators
A 3-phase AI learning plan
Phase 1
Pair programming with AI
- Use a coding assistant for boilerplate, tests and refactoring.
- Give it context: project rules, examples, small steps.
- Review AI code like a colleague's pull request.
Project
Use a coding assistant to write a PowerShell new-hire setup script (drivers, apps, printer mappings), reviewing each suggested block as a pull request, and time it against manual setup.Phase 2
AI in your systems
- Call an LLM API with structured output.
- Retrieval over your own documents or data.
- Evaluate quality, cost and latency before shipping.
Project
Build a retrieval tool over your internal IT manuals and past ticket notes that returns structured JSON fix steps, then measure answer accuracy, cost and latency on 30 real anonymized tickets.Phase 3
Production-grade AI
- Evals and regression tests for prompts.
- Security: prompt injection, data leaks, permissions.
- Monitoring and cost control.
Project
Add an eval suite of 50 ticket prompts with regression tests, prompt-injection checks and permission limits to your helpdesk assistant, and log token cost per resolved ticket weekly.