The Resistance to Network Automation: Understanding the Psychological and Practical Barriers

Network automation has long been heralded as the game-changer that would revolutionize networking. It promises easier management, fewer errors, and more time for strategic, high-value work. Yet, despite these clear advantages, adoption rates remain surprisingly low, with estimates hovering around just 20-30%. Why is this shift, which seems so inevitable, still met with such resistance?

The hesitation to embrace network automation isn’t purely technical—it’s deeply psychological. Many network engineers actively chose this field over programming, yet now find themselves expected to adopt coding and automation skills. This shift triggers a range of anxieties: fear of job loss, concern about losing direct control over networks, and uncertainty about mastering new technical skills. As discussed in a recent episode of The Art of Network Engineering podcast, cognitive biases like loss aversion (where losses feel twice as impactful as equivalent gains) and negativity bias (where negative outcomes seem to outweigh positive ones) significantly shape how engineers perceive automation.

Automation Is Already Here—You Just Don’t Call It That

One of the key insights from the discussion was that network automation isn’t just about writing Python scripts or using Ansible—it’s already present in many engineers’ daily workflows. As Jeff Clark pointed out, even graphical user interfaces (GUIs) are a form of automation, simplifying complex tasks into more manageable steps. These “invisible” automations, such as centralized management tools and wizards, have already become indispensable in modern networking.

Furthermore, learning automation today is easier than ever. AI-powered tools can teach the basics of network automation, dramatically lowering the barrier to entry. In fact, Jeff shared a personal example where, within an hour, he was able to use ChatGPT to guide him through writing an Ansible playbook that automated a task he frequently performed—deploying virtual machines in GNS3. What used to take minutes now happens in seconds.

Small Wins: The Key to Overcoming Resistance

The path to automation adoption isn’t about flipping a switch—it’s about starting small. Rather than tackling massive, organization-wide automation projects, network engineers can begin by automating repetitive tasks that directly impact their own efficiency. Jeff’s experience at Comcast provides a great example: frustrated by a time-consuming ticketing process, he built a simple Excel-based automation that reduced ticket creation time from 15 minutes to just 30 seconds. This not only made his job easier but also led to a broader team-wide adoption of the tool.

The same principle applies today. Whether it’s automating show commands, configuration backups, or simple provisioning tasks, engineers can reclaim time that would otherwise be spent on tedious, repetitive work. As Colin Doyle noted, automation isn’t about replacing jobs—it’s about making work more efficient and freeing up time for higher-value initiatives.

The Future of Network Engineering: From Device Management to Intent-Based Networking

The conversation also highlighted a major shift in networking: the move from managing individual devices to focusing on network-wide service delivery. Tools like Terraform and intent-based networking solutions enable engineers to define desired outcomes rather than manually configuring every node. This evolution represents an inflection point in networking, where automation is no longer just a convenience—it’s a necessity for scaling modern networks.

The fear that automation will replace network engineers is understandable, but history suggests otherwise. The industry has always evolved, and the most successful professionals are those who adapt to new tools and methodologies. Instead of fearing automation, engineers should see it as an opportunity to expand their skill sets, increase efficiency, and gain a deeper understanding of network infrastructure.

Final Thoughts: The Time Factor

Perhaps the most compelling argument for automation isn’t efficiency—it’s time. Engineers who have embraced automation consistently highlight one key benefit: reclaiming hours that would otherwise be spent on mundane tasks. As Daniel Teycheney put it, learning automation means “more time with family, more time for hobbies, more time for life.”

The path forward doesn’t require becoming a programming expert overnight. It starts with small projects that solve real-world problems. Leverage community resources, engage with automation forums, and take advantage of AI-driven learning tools. While resistance is natural, the networking industry is evolving—and those who evolve with it will not only keep their jobs but thrive in a future where automation is a fundamental part of network engineering.

Listen to the episode here: https://www.buzzsprout.com/2127872/episodes/16774037