Network Engineers
Overall Exposure
2025 vs 2023
Theoretical Exposure
69What AI could do
Observed Exposure
37What AI actually does
Automation Risk Score
26Displacement risk
3-Year Outlook (2025 โ 2028)
Projected changes in AI automation metrics over the next 3 years based on estimated data.
Overall Exposure
2025 โ 2028 (estimated)
Theoretical Exposure
2025 โ 2028 (estimated)
Observed Exposure
2025 โ 2028 (estimated)
Automation Risk
2025 โ 2028 (estimated)
Exposure Metrics (2023 - 2028)
Detailed Metrics Table
| Year | Overall | Theoretical | Observed | Risk | Data Type |
|---|---|---|---|---|---|
| 2024 | 48 | 65 | 31 | 22 | actual |
| 2025 | 53 | 69 | 37 | 26 | estimated |
| 2026 | 58 | 73 | 43 | 30 | estimated |
| 2027 | 63 | 77 | 49 | 34 | estimated |
| 2028 | 67 | 80 | 54 | 38 | estimated |
Task Breakdown
About This Occupation
If you work as a Network Engineer, AI is augmenting your configuration and monitoring tasks. With an automation risk of 26/100 and overall exposure at 53%, this role faces medium transformation. Device configuration sees the highest automation at 65%. BLS projects +6% growth through 2034.
Frequently Asked Questions
With an automation risk score of 26%, Network Engineers has a low risk of AI replacement. Most tasks in this role require skills that are difficult for AI to replicate, such as complex decision-making, physical dexterity, or deep interpersonal interaction. AI is more likely to serve as a supportive tool.
The AI automation risk score for Network Engineers is 26% (2025 data). Overall AI exposure is 53%, with 69% theoretical exposure and 37% observed exposure. The risk trend from 2023 to 2025 is 0 points.
The tasks with the highest automation potential for Network Engineers are: Configure and maintain network device settings (65%), Monitor and troubleshoot network performance (58%), Plan and execute network upgrades and migrations (35%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.
The BLS projects +6% employment change for Network Engineers from 2024 to 2034. Combined with an overall AI exposure of 53%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.
Since AI primarily augments capabilities in this role, professionals in Network Engineers should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.