AI and your job: Computer user support specialists
Helps people when their computers, accounts and software stop working, and keeps their equipment running.
Will AI replace computer user support specialists?
No published measure says the job disappears. The US Bureau of Labor Statistics projects employment of computer user support specialists to shrink 3.5 percent, from 750,600 jobs in 2025 to 724,400 in 2035. What AI changes first is tasks, not whole jobs: of the 8 core tasks listed for this work, 5 already show up in AI use data. The practical move either way: learn to direct AI on those tasks and check its work.
What to learn firstThe numbers, with sourcesStart free: lesson 1
The public measures, side by side
Each one answers a different question. None of them is a prediction that your job disappears, and we do not blend them into one score.
Jobs outlook to 2035
The US Bureau of Labor Statistics projects employment of computer user support specialists to shrink 3.5 percent, from 750,600 jobs in 2025 to 724,400 in 2035, with about 39,700 openings a year as people retire or change jobs.
What BLS itself says is changing this job:
- “Sourcing change, capital/labor substitution, share decreases as more businesses offshore their computer user support or solve computer troubleshooting needs using generative artificial intelligence (AI).”
What it does not mean: it is a ten year projection of total jobs, revised every year. It says nothing about any one employer or person.
How people use AI on this work
In Anthropic's Economic Index, conversations about this job's tasks were about 34 percent people working with the AI (learning, iterating, checking) and 66 percent handing a task over to it.
What it does not mean: it describes how people who already use one AI assistant use it, not how many jobs change.
How much of the work AI can assist
Microsoft Research rates this occupation 0.33 on its AI applicability scale of 0 to 1, from what people actually asked an AI assistant to help with.
What it does not mean: its own authors say applicability is not job loss. A high rating means AI can help with much of the work, which is a reason to learn it.
Where AI already shows up in this work
Core tasks of the job, from O*NET, that appear in real AI use. These are the parts of the day that change first.
- Answer user inquiries regarding computer software or hardware operation to resolve problems.
- Read technical manuals, confer with users, or conduct computer diagnostics to investigate and resolve problems or to provide technical assistance and support.
- Oversee the daily performance of computer systems.
- Install and perform minor repairs to hardware, software, or peripheral equipment, following design or installation specifications.
- Maintain records of daily data communication transactions, problems and remedial actions taken, or installation activities.
What stays with people
Core tasks with no AI use observed in the published data. That measures today, not a promise about tomorrow; these are where judgment, trust and presence carry the work now.
- Set up equipment for employee use, performing or ensuring proper installation of cables, operating systems, or appropriate software.
- Confer with staff, users, and management to establish requirements for new systems or modifications.
How long do I have?
Nobody can honestly name a year. The measured pattern so far is that hiring for junior roles slows first in the most exposed work, while people already in the job take on AI assisted tasks. The BLS projection above runs to 2035 and is revised every year.
Stanford's Digital Economy Lab found no widespread displacement, but employment for young workers in the most AI exposed jobs has fallen 19 percent behind comparable peers (August 2026). Read the study.
The practical answer is the same either way: the person who can direct AI on these tasks, and catch it when it is wrong, is the one a team keeps and hires.
What to learn first
In this order, for this job. Each is taught in GAGE's AI literacy program, Certified AI Practitioner: Workplace Foundations.
1.Use AI to diagnose problems from logs and manuals, and confirm the fix yourself
Taught in Module 4, Practical AI Workflow Design and Prompt Engineering; Module 5, Critical Thinking and Context Engineering
2.Help staff use AI tools safely and within the company's policy
Taught in Module 6, AI in the Workplace and Team Leadership; Module 10, AI Security Fundamentals
3.Spot AI phishing and fake help desk calls
Taught in Module 10, AI Security Fundamentals
4.Set up and watch AI helpers and agents with the least access they need
Taught in Module 10, AI Security Fundamentals; Module 12, Bonus: SMB AI Adoption Path
Show an employer you can do it
A course certificate says you finished. At GAGE you explain each idea back in your own words and it is graded against the lesson, so your record shows what you understood. An employer can check it with one link.
Related jobs
Questions
- Will AI replace computer user support specialists?
- No published measure says the job disappears. The US Bureau of Labor Statistics projects employment of computer user support specialists to shrink 3.5 percent, from 750,600 jobs in 2025 to 724,400 in 2035. What AI changes first is tasks, not whole jobs: of the 8 core tasks listed for this work, 5 already show up in AI use data. The practical move either way: learn to direct AI on those tasks and check its work.
- How long do computer user support specialists have before AI changes the job?
- Nobody can honestly name a year. The measured pattern so far is that hiring for junior roles slows first in the most exposed work, while people already in the job take on AI assisted tasks. The BLS projection above runs to 2035 and is revised every year.
- What should computer user support specialists learn about AI first?
- Use AI to diagnose problems from logs and manuals, and confirm the fix yourself; Help staff use AI tools safely and within the company's policy; Spot AI phishing and fake help desk calls. GAGE teaches each of these in its AI literacy program, and the first lesson is free.
Sources
- U.S. Bureau of Labor Statistics, Employment Projections program, Employment Projections, Table 1.2: Occupational projections, 2025 to 35, and worker characteristics, 2025, 2025 to 2035 projections (tables page last modified August 27, 2026). The requested 2024 to 2034 set is superseded; the current table is used., Public domain (bls.gov/opub/copyright-information.htm: everything BLS publishes is in the public domain; cite BLS as the source). Read 2026-09-25.
- Anthropic, Anthropic Economic Index, sixth release (claude_ai, monthly aggregates), release_2026_06_26 (report: Anthropic Economic Index report: Cadences, 2026-06-26; dataset commit 2ea58ff75e4247d26810c37f10c179edc2466cac). Period read: GLOBAL, 2026-05-01 to 2026-06-01, the latest month in the file., CC BY (release_2026_06_26/data_documentation.md: Data released under CC-BY; the repository README says data CC-BY, code MIT. The Hugging Face card metadata says mit, which covers the code.). Read 2026-09-25.
- Microsoft Research (Tomlinson, Jaffe, Wang, Counts, Suri), Working with AI: Measuring the Applicability of Generative AI to Occupations (AI applicability scores), v1.1 (arXiv 2507.07935 revision v6), repository commit c94a07c52fb1d88ca5d221388f06d10e1bd6d2fe of 2025-12-22. Bing Copilot conversations, United States, 2024-01-01 to 2024-09-30., CC BY 4.0 (LICENSE.txt and README: This repository is licensed under CC BY 4.0). Read 2026-09-25.
- National Center for O*NET Development, for the U.S. Department of Labor, Employment and Training Administration, O*NET 31.0 Database: Task Statements and Task Ratings, O*NET 31.0 (August 2026, the current production release per onetcenter.org/db_releases.html on 2026-09-25), CC BY 4.0 (onetcenter.org/database.html: licensed under a Creative Commons Attribution 4.0 International License). Read 2026-09-25.
- This page includes information from O*NET OnLine by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0 license. O*NET is a trademark of USDOL/ETA. GAGE has modified all or some of this information; USDOL/ETA has not approved, endorsed, or tested these modifications.
- Occupation code 15-1232. The skills, task grouping and plain language on this page are GAGE's own.