Douglas Murray is the chief executive officer at Auvik.
I’ll say it: I’m old (or so my wife tells me). When I entered the workforce, data communications revolved around technologies like ATM and Frame Relay. With the introduction of the Cisco Catalyst 6500 series and the growing adoption of IP networking, the way the world connected began to change.
I witnessed those changes firsthand over the course of my career in tech. When I earned my Cisco Certified Internetwork Expert (CCIE) certification, knowing a network also meant knowing its architecture at a physical level, port by port. Today, the deep, specialized networking expertise that defined my generation is becoming increasingly rare.
To put this in perspective, think about how many students coming out of university today go on to pursue networking certifications like the CCIE or JNCIE.
As veteran specialists with decades of networking experience leave the workforce, fewer professionals with the same depth of networking expertise are stepping in to replace them. At the same time, the role of the IT professional has become much broader. Talent shortages, tool sprawl and rapidly changing technology have helped solidify the rise of the IT generalist, someone who must possess knowledge across a wide range of IT functions rather than specializing in a single silo.
This shift toward IT generalists has reshaped what an IT career looks like. Organizations now hire for roles like cloud engineer, platform engineer and site reliability engineer, positions that often span multiple areas of infrastructure, including networking, security and operations. In many cases, the specialized knowledge that once sat with individuals deeply focused on the network now has to be shared across broader IT teams managing many other responsibilities at the same time.
The Role Has Changed, But Network Complexity Remains
With AI, cloud adoption, SaaS and automation, day-to-day work has been steadily pulled away from racks, consoles and physical infrastructure. The network itself, however, hasn’t become simpler, even though the way we manage it has advanced considerably. A typical environment today spans multiple vendors, each with its own operating systems, commands and conventions.
One persistent challenge within that complexity is visibility. Despite advances in tooling and growing IT budgets, my company’s 2026 report found that 27% of IT professionals still cite network visibility as a top challenge. At the same time, modern networks must support an increasingly diverse mix of infrastructure, devices and applications, creating more dependencies to manage and secure. All of this is happening amid evolving cybersecurity threats and IT staffing shortages.
These ongoing hurdles explain why many businesses are turning to AI. Across the market, vendors are using AI to help IT teams navigate the complexity of network management and resolve issues faster through automation. But being able to manage something through an AI tool does not automatically translate to understanding it. That distinction matters all the more for teams without a dedicated network specialist.
What The Retiring Generation Will Take With Them
Historically, much of network knowledge lived with specialists who could recognize what a healthy network looked like, distinguish urgent issues from background noise, diagnose root causes and determine the best course of action for a specific environment. That level of fluency typically takes years of practice to build, and it’s growing scarcer.
As many network specialists approach retirement age, their deep network knowledge and the judgment it enables still need to exist somewhere within the organization. This has already become an urgent issue for many IT leaders: Earlier this year, Enterprise Management Associates reported that 52% of organizations are struggling to hire and retain network engineers in 2026, up from 26% in 2022.
An organization might not be able to control the structural changes reshaping the IT workforce, but it can decide where its institutional knowledge goes. With the right technology, role design and skill development, organizations can extend network fluency across their IT teams. AI has an important role to play in carrying the expertise forward, although not as a black box that simply tells teams what to do or autonomously executes actions without transparency into how those decisions are made.
Giving That Knowledge A New Home
Instead, AI can offer organizations a way to preserve and extend at least some of that expertise by taking knowledge that once required years of specialized experience and putting it in front of the broader IT team at the moment it’s needed. By bringing together network context, correlating signals to surface likely root causes and explaining not just what to do next but why, AI can help IT generalists approach problems from a specialist perspective.
Over time, that guidance can deepen their understanding of network issues and sharpen their troubleshooting instincts. The goal is to make network-speak accessible to IT professionals at every level, giving them the knowledge and insights they need to make informed decisions, even without years of specialization in the field.
My generation learned to “speak network” through years of hands-on experience. The task before us now is to ensure that expertise outlives us and continues to grow in the next generation.
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