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AI exposure report

Will AI replace Computer Network 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

50/100

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 score

Will AI replace Computer Network Support Specialists?

Not entirely. Today's AI tools can take on about 50% of the typical work in this occupation, mostly: document help desk requests and resolutions. The parts that stay human include: Troubleshoot network or connectivity problems for users or user groups.; Perform routine maintenance or standard repairs to networking components or equipment.; Identify the causes of networking problems, using diagnostic testing software and equipment..

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.

TaskAutomatable
Document help desk requests and resolutions.AI already used 82%
Evaluate local area network (LAN) or wide area network (WAN) performance data to ensure sufficient availability or speed, to identify network problems, or for disaster recovery purposes. 60%
Provide telephone support related to networking or connectivity issues. 60%
Identify the causes of networking problems, using diagnostic testing software and equipment. 50%
Troubleshoot network or connectivity problems for users or user groups.AI already used 47%
Perform routine maintenance or standard repairs to networking components or equipment. 20%

+ 20 more tasks (56% of the week) in the full test.

Your human edge

  • Troubleshoot network or connectivity problems for users or user groups.
  • Perform routine maintenance or standard repairs to networking components or equipment.
  • Identify the causes of networking problems, using diagnostic testing software and equipment.

AI tools to try

Coding assistants (GitHub Copilot, Claude Code, Cursor)ChatGPT / Claude for design and debuggingAI test and documentation generators

Related roles

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 and refactor a Python script that pulls running configs from 10 routers and diffs them against a golden template, reviewing every line before merging.

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 sanitised network runbooks and switch configs that returns structured JSON triage steps for a reported outage, and measure accuracy, cost and latency on 20 past tickets.

Phase 3

Production-grade AI

  • Evals and regression tests for prompts.
  • Security: prompt injection, data leaks, permissions.
  • Monitoring and cost control.

Project

Harden that triage assistant with a 30-case regression eval suite, prompt-injection and config-secret leak tests, and a monthly token budget alert; report before/after pass rates.
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