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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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The AI Resilience Report is a project from CareerVillage®, a registered 501(c)(3) nonprofit.
Mostly Resilient
Last Update: 4/23/2026
Your role’s AI Resilience Score is
59.0%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Low
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
High
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
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.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forComputer Network Architects
Computer Network Architects are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
The career of a Computer Network Architect is labeled as "Mostly Resilient" because while AI tools are increasingly used to automate routine tasks like monitoring network performance and troubleshooting basic issues, the core responsibilities still require human expertise. Tasks such as planning, design, and making strategic decisions rely on human judgment and cannot be easily replaced by AI.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is mostly resilient
The career of a Computer Network Architect is labeled as "Mostly Resilient" because while AI tools are increasingly used to automate routine tasks like monitoring network performance and troubleshooting basic issues, the core responsibilities still require human expertise. Tasks such as planning, design, and making strategic decisions rely on human judgment and cannot be easily replaced by AI.
Read full analysisAnalysis of Current AI Resilience
Network Architects
Updated Quarterly • Last Update: 2/17/2026
How is AI changing Network Architects jobs?
Network architects’ routine tasks are increasingly helped by AI-powered tools. For example, vendors now offer platforms that use AI to watch network data and spot issues in real time. One news report describes an AI-based system that “swiftly detects and resolves customer issues and network anomalies in real time,” giving operators immediate insights [1].
Likewise, experts say next-generation monitoring (“observability”) tools will not only show problems but even suggest or apply fixes automatically [2]. In short, many repetitive jobs like parsing performance reports or predicting capacity needs can be partly automated by AIOps (AI for IT operations) systems [3] [2].
By contrast, tasks that rely on human learning and communication remain human-led. We found no examples of AI replacing activities like visiting vendors, going to conferences, or reading new research. These rely on judgment, relationships and strategy.
Industry analysts note that companies still depend on skilled IT advisors and staff to make networking decisions and guide technology changes [2]. In other words, AI tools today help pick out and even fix low-level network problems, but architects continue to handle planning, design and training tasks.
Sources
How fast is AI adoption growing for Network Architects?
AI networking tools are commercially available and growing in use. Many companies see clear benefits: for instance, one supplier claims its AI monitoring can cut help-desk triage time “drastically,” saving time and money [1]. Surveys show a high level of interest – e.g. a McKinsey report found about 77% of firms are using or exploring AI in business [3], and in networking specifically a 2025 study noted 65% of partners were developing AI-driven network automation services [2].
These tools can reduce manual workload, speed up problem-solving and improve efficiency, so there is pressure (especially when trained network specialists are scarce) to adopt AI solutions [3] [2].
At the same time, adoption is cautious. Networking is complex and critical, so firms worry about costs and risks. Experts point out that “infrastructure-as-code” approaches are still maturing in networks, since networks are often less flexible than cloud systems [2].
High setup costs, data-quality issues and security concerns also slow adoption – for example, one report cites that about 30% of AI projects can stall due to such challenges [3]. In summary, AI for network management is available and offers clear economic value, but companies balance those gains against implementation costs, potential errors, and the need for human oversight [1] [2].
Sources
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More Career Info
Career: Computer Network Architects
They design and build the systems that allow computers to communicate with each other, making sure information flows smoothly and securely within organizations.
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Similar Careers
Employment & Wage Data
Median Wage
$130,390
Jobs (2024)
179,200
Growth (2024-34)
+11.9%
Annual Openings
11,200
Education
Bachelor's degree
Experience
5 years or more
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 network computer-aided design (CAD) software packages to optimize network designs.
2
Prepare design presentations and proposals for staff or customers.
3
Explain design specifications to integration or test engineers.
4
Supervise engineers or other staff in the design or implementation of network solutions.
5
Evaluate network designs to determine whether customer requirements are met efficiently and effectively.
6
Adjust network sizes to meet volume or capacity demands.
7
Prepare detailed network specifications, including diagrams, charts, equipment configurations, or recommended technologies.
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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