The demand for network engineers was already acute. Now, organizations are losing engineers due to retirement, burnout and a shift in required skills.
In a recent Opengear study, 86 percent of U.S. IT leaders said they expect at least 25 percent of their network engineering staff to retire within five years. Almost all engineers have reported increased workloads, further fueling burnout and turnover.
The loss of experienced professionals threatens network reliability. The talent shortage is also creating security risks and contributing to delays in critical infrastructure and digital transformation projects.
The industry is facing a significant shift, prompting a need for advanced network intelligence to handle operations. AI is transforming network automation by moving from static, script-heavy management to autonomous, self-healing systems. Gartner predicts that by 2027, 70 percent of network operations staff will rely on AI for “Day 2” network management, up from less than 5 percent in early 2024.
Most organizations have automated network management to some extent. However, they typically rely on traditional scripted automation and playbooks. Worse, techniques such as network configuration and change management address as little as 10 percent of the total network management effort. More than two-thirds of network management activities still involve error-prone manual processes.
There is significant cultural resistance to changing how networks are managed, with many teams preferring to stick to familiar device-centric methods. Network engineers often lack the necessary software development skills to transition to modern NetDevOps approaches.
The perceived risk of automating complex, multi-vendor environments keeps organizations in “firefighting” mode, relying on manual, device-by-device management. Many organizations, especially in conservative sectors, hesitate to change functioning network processes, even if they are inefficient.
However, reality is forcing organizations to accelerate their network automation initiatives. Many IT teams are struggling to manage more network devices and greater complexity with fewer resources. Manual processes simply can’t scale to meet this demand. Without automation, organizations face significant operational risk.
AI-powered automation improves resilience by predicting, detecting and remediating issues in real time. Machine learning analyzes historical data and telemetry to forecast equipment failures or performance bottlenecks before they cause downtime. If an anomaly or fault is detected, AI can automatically trigger remediation steps without human intervention.
IT teams are also using AI to automate and optimize network configurations. Intent-based networking allows network engineers to define high-level business goals while AI determines and applies the necessary technical configurations.
Increasingly, organizations are moving beyond simple automation toward agentic AI. AI agents can reason and execute multistep tasks with minimal supervision, enabling them to analyze real-time telemetry, troubleshoot problems, optimize traffic and secure infrastructure across complex networks. Garner predicts that by 2030, AI agents will be the primary approach for executing network runtime activities.
While traditional network engineering roles are decreasing, the demand for network professionals is actually increasing. The role is shifting from manual configuration to coding, scripting and using AI for efficiency. The future of the field involves NetDevOps, which applies DevOps principles — automation, continuous integration/deployment and software development approaches — to network operations.
Organizations are using multiple strategies to bridge the skills gap. Many are actively upskilling network engineers and offering bonuses for gaining new skills. Some are pairing network engineers with software developers to share knowledge and build collaborative teams.
Partnering with a qualified technology provider can help ease the transition to AI-powered automation. Technologent’s Secure Connectivity practice is designed to help organizations build smarter networks that incorporate advanced automation. Our networking team works closely with our AI team to help organizations move toward an autonomous, “lights out” environment. If your network engineers are bogged down in manual processes, contact one of our experts to start your journey toward AI-powered automation.