en.Wedoany.com Reported - AI is transforming how network engineers work. Executives from Verizon, Telstra, and other companies, along with industry analysts, point out that the role of network engineers is shifting from device configuration to intent definition, system oversight, and agent governance.
Sid Nag, President and Chief Research Officer at research firm Tekonyx, stated that full autonomy does not mean complete absence of human supervision. Anil Guntupalli, Senior Vice President of Technology and Product Engineering at Verizon, noted that the company is progressing from Level 3 automation to Level 4 automation while maintaining human oversight throughout. Regan Ireland, Global Head of Pre-Sales Solutions at Telstra, indicated that higher automation requires network engineers to have a broader perspective, where the key is no longer configuring devices but defining intent, guardrails, constraints, and the parameter ranges for autonomous system decision-making. Rule-setting is becoming the core of network engineering expertise.
The traditional model of the Network Operations Center (NOC) is coming to an end. Sid Nag said the NOC is no longer a ticket handling and troubleshooting center but is evolving into an AI operations command and control center responsible for overseeing various agents. New roles are emerging around agent governance, policy design, anomaly handling, and autonomous operations engineering. Guntupalli pointed out that engineers who once spent significant time on configuration are now focusing on more complex issues. Last year, Verizon automated 70 million network configuration changes. A TM Forum report shows that some Communications Service Providers (CSPs) that have reached Level 4 autonomy can resolve 95% of fault tickets without human intervention.
Future engineers will need to understand the behavior of the entire system, rather than being limited to specific domains or device categories. Ireland stated that this trend requires engineers to possess systems thinking and work at the level of abstraction and orchestration. Sid Nag believes that as agents take on operational responsibilities within the network, agent governance becomes a specialized discipline. The associated responsibilities fall on the organization that designs, approves, and governs the agent, which has no precedent in previous generations of network operations. Data observability is a prerequisite for achieving automation. Ireland emphasized that clean telemetry data and controlled sources of truth are critical for automated tasks. Gartner data shows that among organizations that have encountered AI setbacks, 38% cite poor data quality as the direct cause of failure. This is partly why most operators remain between Level 0 and Level 1 autonomy. As networks evolve toward software-led models, Ireland noted that teams require different skill sets, which involves cultural education and skills training.
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