The talent pipeline for network engineering and operations teams is running dry. AI might soften the pain of this people shortage, but ultimately it could make things worse.
Since 2022, Enterprise Management Associates (EMA) has been polling IT professionals about the state of the network engineering labor market. In 2022, 26% told us that they were struggling to hire networking pros. In 2024, that number increased to 41%. This year, 52% told us they are struggling to hire and retain network engineers, according to EMA’s Network Management Megatrends 2026 report.
“We’re trying to hire a senior engineer and an intermediate person—people with 10 to 15 years of experience—but all we’re seeing is very high-level resumés—people who have 25 years of experience and multiple CCIEs,” said a network architect with a multi-national bank. “And all the junior-level people are very junior. None of them is qualified for anything other than site support. They’ve never done any implementation, other than running a couple of commands to make sure a site is up. The security team is struggling, too.”
EMA’s research found that three skills are especially hard for IT organizations to find in the labor market:
- Network security
- Networking for AI applications
- Network automation
In other words, IT organization can’t find people to secure their networks. Building and managing networks for their AI projects will be difficult. And implementing automation to ease this talent gap will also be hard.
Why is a Good Network Engineer Hard to Find?
Why are companies struggling to hire networking pros?
First, a generation of engineers is cruising into retirement. A statistic has been making the rounds on social media recently: 25% of network engineers will retire over the next five years. When people use this stat, they rarely cite the source. I tracked it down. It’s from a 2023 OpenGear survey, which found that 86% of CIOs expect 25% of network engineers to retire within five years. It’s unclear what the other 14% of CIOs were thinking. What is clear is that three of those five years have passed us by. We’re already deep into the retirement wave that this survey predicted.
My conversations with network engineers and architects confirm this stat. Many IT organizations are seeing retirements at the top of their network engineering teams, and filling these empty seats with up and coming talent is painful.
As older engineers sign off and ship out, the labor market is struggling to replenish the talent pipeline. Network engineering is apparently not an appealing specialization. Public cloud adoption has shrunk on-premises infrastructure, and networking is perceived incorrectly as strictly an on-premises technology. Over the last decade, people pursuing a tech career have gravitated toward growth areas like DevOps and cloud engineering. More recently, workers young and old have pivoted toward AI careers, where all the money is these days.
Solving the Skills Gap
EMA’s Megatrends research revealed that most IT organizations are addressing the talent shortage in a few ways. First, 61% believe that AI-driven network management solutions can help. For example, network management vendors have introduced agentic capabilities that can detect, analyze, and remediate problems with or without human intervention. In theory, lower-skilled personnel can tackle more complex tasks with AI assistance, and senior-level engineers can work more efficiently with AI.
Nearly 60% of IT organizations are training and upskilling existing personnel to fill advanced technical roles. “We had an architect role open for half a year, and we were unable to find someone. We ended up hiring someone internally and training him ourselves.” a network observability and automation architect at a Fortune 500 retailer recently told me.
Finally, 54% of organizations are adopting network automation and orchestration tools to reduce manual work and free up engineering resources. However, this latter tactic will be challenging, given that network automation skills are in short supply.
While AI and network automation can act as force multipliers for the limited number of experienced engineers that organizations have, it won’t help them fill the job openings they need to fill today. And AI will never replace senior network engineers and architects. IT organizations will always want human experts calling the shots.
Don’t Let AI Choke Off Your Talent Pipeline
While CIOs might see AI as a panacea for labor market challenges, EMA is seeing evidence that AI will make the network engineering labor market even more challenging for employers. The network operations center (NOC) has long been the traditional training ground for engineering talent, and those jobs are threatened.
“The long-term goal is to reduce our reliance on tier-1 NOC engineers and eliminate junior-level roles by improving our monitoring and automation of incident management,” said the network observability and automation architect at a Fortune 500 retailer.
“Instead of having bigger and bigger NOCs, management is looking to make processes more efficient and more automated, where you can achieve the same tasks with fewer people,” said a network tools architect with a Fortune 500 media and entertainment company. “What used to be run by a 25-person team, they now want to run with a 10-person team.”
NOCs traditionally produce future engineers. These junior technicians learn on the job by triaging events and collaborating with senior engineers to solve problems. If AI and automation eliminate these junior NOC roles, where will the future engineers come from?
IT organizations are starting to worry about this issue. A recent survey of 152 IT and cybersecurity decision-makers by EMA found that 72% were at least somewhat concerned that AI’s ability to replace entry-level IT and cybersecurity roles would negatively impact their company’s ability to develop engineering talent internally.
Rather than cutting headcounts, CIOs should be thinking about cultivating these junior tech workers. They should instruct middle management to identify NOC personnel who show promise and make sure that those people receive mentoring and training. If organizations do adopt AI-driven network management solutions, they should investigate how those tools can empower junior personnel, rather than make them redundant.
I’m planning new research later this year. I will do a deep dive survey of IT management about what they’re doing to address engineering talent shortages and how they are adopting AI and automation to solve the talent crisis, rather than make it worse. If you’d like to learn more, email me.
