BETA
Updated: Mar 20
BETA
Updated: Mar 20
Evolving
Last Update: 3/13/2026
Your role’s AI Resilience Score is
33.1%
Median Score
Changing Fast
Evolving
Stable
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
Computer Systems Analysts
They improve how companies use computers by studying their systems, finding problems, and suggesting solutions to make everything work better.
This role is evolving
The career of a computer systems analyst is labeled as "Evolving" because AI tools are increasingly being used to help with routine tasks like monitoring system performance and spotting problems quickly. However, analysts still need to use their creativity and judgment for tasks like designing systems and training people, which AI can't fully do.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is evolving
The career of a computer systems analyst is labeled as "Evolving" because AI tools are increasingly being used to help with routine tasks like monitoring system performance and spotting problems quickly. However, analysts still need to use their creativity and judgment for tasks like designing systems and training people, which AI can't fully do.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
CareerVillage's proprietary model that estimates how resilient each occupation's tasks are to AI automation and augmentation
Changing fast16.0%
16.0%
Microsoft's Working with AI
AI Applicability
Measures how applicable AI tools (like Bing Copilot) are to each occupation based on real usage patterns
Changing fast10.9%
10.9%
Anthropic's Observed Exposure
AI Resilience
Based on observed patterns of how Claude is being used across occupational tasks in real conversations
Changing fast20.7%
20.7%
Will Robots Take My Job
Automation Resilience
Estimates the probability of automation for each occupation based on research from Oxford University and other academic sources
Evolving42.8%
42.8%
Althoff & Reichardt
Economic Growth
Measured as "Wage bill" which is a long term projection for average wage × employment. It's the total labor income flowing to an occupation
Stable72.6%
72.6%
High Demand
Labor Market Outlook
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
8.7%
Growth Percentile:
90.1%
Annual Openings:
34,200
Annual Openings Pct:
77.5%
Analysis of Current AI Resilience
Computer Systems Analysts
Updated Quarterly • Last Update: 2/17/2026
What's changing and what's not
In practice, many technical parts of a systems analyst’s job are now aided by AI tools. For example, so-called “AIOps” platforms use machine learning to watch system performance and spot problems automatically [1] [1]. This means routine monitoring, testing and alerting can happen faster – the AI sifts through logs and metrics to flag issues like slowdowns or security threats.
New AI helpers also find bugs in code. For instance, OpenAI’s Aardvark can scan code for vulnerabilities and suggest fixes (though a person still reviews them) [2], and DeepMind’s CodeMender can even patch security bugs in code [1]. In testing work, generative AI can draft test scripts from simple prompts [1].
Early studies report that many tech teams already use AI in testing, but experts stress that humans must still “keep context and integrity front and center” [1] [1]. In one view, “AI should augment testers, not replace them” [1].
Other tasks remain mostly human jobs. Choosing new software or hardware, designing whole systems, training people, and leading projects involve creativity and judgment. We didn’t find examples of AI fully doing those tasks.
For now, analysts still do the research, planning and face-to-face teaching that machines can’t easily replicate. In short, simple data checking and problem-spotting are increasingly automated by AI tools, while strategy, design and supervision still rely on human insight.
Sources
AI in the real world
AI tools for IT work are growing more available, but adoption will depend on costs, benefits and trust. On one hand, cloud AI services and open-source models make it easier to try AI for things like monitoring and testing. Many companies plan to invest more in AI soon – one report found over 60% of organizations intend to boost AI use in projects by 2025 [3].
This is because AI can improve efficiency (for example, fixing issues faster [1]) and help where skilled analysts are in short supply.
On the other hand, AI brings challenges. It can be expensive to set up good AI systems and to train people to use them. Some tech workers still worry about accuracy.
A recent survey noted that while most developers use AI tools daily, about one-third distrust AI-generated results [1]. In fields like systems work, mistakes can be costly, so teams are cautious. Finally, there are few big social or legal barriers in IT (unlike in medicine or law), so using AI is generally accepted, as long as human experts stay involved.
Overall, routine tasks are being automated quickly, but firms tend to roll out new AI tools carefully, keeping skilled analysts “in the loop” to handle complex decisions [1] [2].
Sources
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More Career Info
Career: Computer Systems Analysts
Parent Careers
Similar Careers
Employment & Wage Data
Median Wage
$103,790
Jobs (2024)
521,100
Growth (2024-34)
+8.7%
Annual Openings
34,200
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Use object-oriented programming languages, as well as client and server applications development processes and multimedia and Internet technology.
2
Supervise computer programmers or other systems analysts or serve as project leaders for particular systems projects.
3
Analyze information processing or computation needs and plan and design computer systems, using techniques such as structured analysis, data modeling and information engineering.
4
Train staff and users to work with computer systems and programs.
5
Use the computer in the analysis and solution of business problems, such as development of integrated production and inventory control and cost analysis systems.
6
Expand or modify system to serve new purposes or improve work flow.
7
Specify inputs accessed by the system and plan the distribution and use of the results.
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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