Mostly Resilient

Last Update: 8/30/2026

AI Resilience Score for Computer Occupations (misc):

52.2%

Median Score

Meaningful human contribution

Low

Long-term employer demand

High

Sustained economic opportunity

High

Our confidence in this score:
Medium-high

Contributing sources

Methodology and Scoring Rationale

To score how resilient miscellaneous computer occupations is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For miscellaneous computer occupations, 6 of 8 sources had data. The AI exposure sources largely agreed: AI Resilience Model, Anthropic, and Microsoft all rated human contribution as low, while OpenAI Signals landed at medium, nudging confidence to medium-high. Strong hiring and pay signals pushed the score up, landing this career at "Mostly Resilient."

AI Resilience Report forComputer Occupations, All Other

$116,580 median salary27,000 annual openingsSOC Code: 15-1299.00

Computer Occupations, All Other are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.

This career earns a "Mostly Resilient" label because, while AI is genuinely taking over a lot of the repetitive tasks (like monitoring logs, flagging errors, and routine system maintenance), humans are still needed to supervise those AI tools, handle unexpected problems, and make judgment calls when things go wrong. The role is shifting more than disappearing, moving from "person who runs the computers" to "person who oversees the AI that runs the computers," which actually keeps skilled workers in the picture.

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This role is mostly resilient

This career earns a "Mostly Resilient" label because, while AI is genuinely taking over a lot of the repetitive tasks (like monitoring logs, flagging errors, and routine system maintenance), humans are still needed to supervise those AI tools, handle unexpected problems, and make judgment calls when things go wrong. The role is shifting more than disappearing, moving from "person who runs the computers" to "person who oversees the AI that runs the computers," which actually keeps skilled workers in the picture.

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Analysis of Current AI Resilience

Computer Occupations (misc)

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Computer Occupations (misc) jobs?

The tasks that make up this catch-all computer job — logging system events, watching for errors, running data through spreadsheets, and keeping hardware humming — are exactly the kinds of repetitive digital chores that today's AI is best at. A category called "AIOps" (AI for IT operations) is now moving from monitoring dashboards to actually fixing things on its own. According to a summary of Gartner's 2026 Hype Cycle for AI in IT Operations, a quarter of the work performed by IT infrastructure and operations people will be handled by AI by 2030 [1], and 60% of enterprises will deploy agentic AI in IT operations by 2029, up from fewer than ten percent today [1].

SHRM's 2026 research puts real numbers behind this: computer and mathematical occupations already have the highest share of employment with at least 50% of tasks automated, at 51.2% [2]. Most of this is augmentation today — AI drafts runbooks, analyzes logs, and suggests fixes while a human clicks "approve" — but the balance is tipping. Gartner expects that by 2029 only 20% of AI-suggested actions will need human approval, down from 80% in 2025 [1].

Data center operators are seeing the same shift, with new tools automating electrical, cooling, physical security, and daily administration [3] tasks that used to require a human on shift.

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AI Adoption

How fast is AI adoption growing for Computer Occupations (misc)?

Adoption is moving fast because the software is cheap compared to 24/7 staffing, and vendors ship AIOps features built into products companies already own. ACM's own career digest reports that tech businesses have cut more than 123,000 jobs so far in 2026, a year-over-year increase of 66%, with AI the most common factor driving the cuts [4], and TechCrunch has been keeping a running list of major tech layoffs in 2026 where employers cited AI [5]. But there are real brakes, too.

Gartner warns that by 2028, 40% of I&O organizations using agentic AI at scale will experience a business-critical service disruption, up from less than 1% in 2026 [1] — meaning trust, safety, and compliance concerns will keep humans in the loop for supervising, training junior operators, and handling weird edge cases. The good news for young people: those uniquely human skills — judgment, coordinating people, explaining problems clearly, and taking responsibility when something breaks — are exactly what SHRM identifies as nontechnical barriers that slow displacement [2]. If you're curious about this field, learning to direct AI agents (prompt engineering, guardrail design, incident response) is a smart bet, because the role is shifting from "operating computers" to "supervising the AI that operates computers."

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Will AI replace Computer Occupations (misc)?

Will AI replace Computer Occupations (misc)?

No. We don't think AI will replace Computer Occupations, All Other, though we do expect the job to change.

Our 52.2% AI Resilience Score reflects a real tension: the routine digital tasks at the core of this role, things like monitoring logs, running diagnostics, and keeping hardware running, are exactly what AI is built to absorb. Computer and mathematical occupations already have the highest share of workers with at least half their tasks automated [2], and a category called AIOps is moving fast from flagging problems to fixing them without human input [1].

What keeps this role alive is the part AI still handles poorly. Judgment calls when something breaks in an unexpected way, explaining a failure to a nervous manager, deciding whether to trust an AI-suggested fix on a critical system: those stay human. Gartner expects that by 2028, four in ten organizations using agentic AI at scale will experience a serious service disruption [1], which means someone still has to supervise, audit, and take responsibility.

The economic picture supports cautious optimism. Employer demand and earning potential both score well in our analysis. The smart move for anyone entering this field is learning to direct AI agents rather than just operate systems. The job is shifting, not disappearing.

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Latest AI news for Computer Occupations (misc)

These articles highlight how AI is transforming "Computer Occupations, All Other" by reshaping job roles and expectations. For instance, the article from MTU discusses how AI is creating new opportunities while also changing traditional roles, emphasizing the need for adaptability. The Goldman Sachs piece reassures that while AI may disrupt, it will also create new jobs, suggesting a balanced outlook. Students can leverage this information to cultivate AI resilience, preparing for a future where they can thrive amidst these changes.

More Career Info

Career: Computer Occupations, All Other

They solve unique computer problems by designing and maintaining systems or software, ensuring technology runs smoothly in ways not covered by other specific computer jobs.

Employment & Wage Data

Median Wage

$116,580

Jobs (2025)

471,200

Growth (2025-35)

+5.1%

Annual Openings

27,000

Education

Bachelor's degree

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

70% ResilienceCore Task

Supervise and train peripheral equipment operators and computer operator trainees.

2

45% ResilienceCore Task

Load peripheral equipment with selected materials for operating runs, or oversee loading of peripheral equipment by peripheral equipment operators.

3

40% ResilienceCore Task

Oversee the operation of computer hardware systems, including coordinating and scheduling the use of computer terminals and networks to ensure efficient use.

4

35% ResilienceCore Task

Help programmers and systems analysts test and debug new programs.

5

32% ResilienceCore Task

Notify supervisor or computer maintenance technicians of equipment malfunctions.

6

30% ResilienceCore Task

Answer telephone calls to assist computer users encountering problems.

7

28% ResilienceCore Task

Enter commands, using computer terminal, and activate controls on computer and peripheral equipment to integrate and operate equipment.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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