Can AI Replace Network Engineers?

The hype around ChatGPT and other flashy new AI tools has prompted speculation about machines replacing human jobs. For network engineering, based on theresanaiforthat.com it is estimated that over 4000 AI applications could automate 55% of the roughly 1000 core tasks. But can AI truly replace the various roles and responsibilities within the network engineering field?

In this post, I'll examine that question by looking at the different roles, required skills, and lifecycle stages that make up network engineering. People often oversimplify with a blanket "Can AI replace X" question. By breaking the profession down into the Who, What, and When, we can develop a more nuanced answer.

Who Works in Networking

First, the Who - the common network engineering roles. At the entry level, network technicians handle physical cabling and basic device racking and stacking. Junior network engineers configure and monitor network devices while assisting with issues like connectivity problems and performance troubleshooting.

Network engineers handle more advanced tasks like configuring routers, switches and security appliances, scripting management and automation of the network, and ensuring high availability. Senior network engineers tackle complex network designs, provide guidance and review for junior peers, and oversee critical infrastructure projects.

At the top, network architects develop the overall technology strategy, design the overarching architecture, and work closely with business stakeholders on long-term planning.

What Skills for Each Role

Now the What - the important skills required for each role. Network technicians require knowledge of cabling, racking, power distribution, and basic hardware troubleshooting. Junior engineers need to understand fundamental router/switch configuration, monitoring, and have solid problem solving abilities for common network disruptions.

Network engineers must master complex routing protocols like OSPF and MP-BGP, various routing policy techniques, switching techniques like VLANs and spanning tree, network virtualizations, tunnelings and the overlays such as VXLANs, GRE, and MPLS, Software Defined Networking, Quality of Services, security topics like access control and VPNs, and have scripting skills for automation and monitoring. Senior network engineers need all the same knowledge but at a deeper level, plus skills in designing complex and resilient network architectures, leading teams, and guiding technology strategy.

Network architects require a blend of technical depth, business acumen, and interpersonal skills to drive consensus on optimal network strategies and designs across stakeholders. And excellent communication skills to translate technology capabilities into business impact.

When to Work in Network Lifecycle

Finally, the When - mapping professional roles to the network lifecycle. Cisco's PPDIOO model outlines the stages as Prepare, Plan, Design, Implement, Operate, and Optimize.

In the Prepare phase, architects play the lead role in establishing requirements and drafting the overarching network strategy and architecture. The Plan phase involves capacity planning and gap analysis. Architects and senior engineers assess facilities, requirements, and existing infrastructure.

The Design phase is where senior network engineers shine by developing the comprehensive technical specifications for security, performance, redundancy, and integration based on the architectural direction. Junior engineers play a supplementary role with simple design components.

During Implementation, the network engineers configure and activate all devices according to the design documents. Testing and cutover checkouts before operational turnover require broad team involvement.

The Operate phase relies heavily on the network engineer and below roles for day-to-day monitoring, maintenance, and troubleshooting to keep systems humming. The Optimize phase allows senior engineers opportunities to analyze performance, automate operations, and identify improvement opportunities in the environment.

AI Impacts to Network Engineers

Looking at the interplay of roles and lifecycle stages makes the potential AI impacts clearer. The junior engineer and network engineer roles are most susceptible to automation. As AI matures, fewer humans will be needed for basic design work, equipment configuration and network monitoring. However, complex problem solving and strategic guidance still require human ingenuity.

Network architects will remain heavily involved throughout the process. And senior engineers will always be needed to handle intricate design challenges, optimize large-scale automation, and mentor junior team members. While AI will reshape aspects of network engineering, a human-machine partnership model is the likely path forward rather than wholesale replacement.

The biggest pinch will be felt at the entry level. Some companies may continue relying on human-driven processes, providing onboarding opportunities. But others are aggressively automating, reducing the need for junior networking roles. With fewer junior-level network engineering roles available due to automation, gaining the necessary hands-on experience to advance to higher-level positions is becoming extremely difficult, creating a frustrating catch-22 situation for newly skilled candidates looking to enter the field.

My advice to aspiring network engineers is to learn automation, scripting, and infrastructure-as-code techniques as early as possible. Gain hands-on experience by building home labs, creating virtual networks, and automating every task you can. While steep, overcoming the experience catch-22 will be crucial to thriving in our AI-driven future.