Can AI Replace Network Engineers? A Real-World Perspective from the Trenches

Today, I watched the latest YouTube video by NetworkChuck.
He discussed how AI is affecting network engineers. It was really interesting — and it motivated me to continue my journey as a network engineer.

Of course, I’m facing some difficulties right now.
If you have any open positions for network engineers, please feel free to message me anytime. I’d really appreciate it.

I’m currently based in the UK.
Yes, I could join Amazon — I mean, Amazon Flex.
No joking. I’m serious.


Right now, I’m especially interested in data center networking and hyperscale networking for AI.
Regardless of the use case — whether it’s business, research, or something more creative like cryptocurrency — I find these areas fascinating.

Also, Internet route checking (RPKI again? Yes, definitely) is something I want to explore further.


On the topic of device deployment — automation, zero-touch provisioning, scripting, etc.:

Yes, scripting in Bash or Perl (SSH into the device, wait for a prompt, automate the commands) has been used for a long time. But today, there are many modern approaches: agents, tailored remote access methods, tunneling deployments, and more.

How do they compare? Which method is best?
Ansible? Python scripting? YAML? Network programming?

And… you prepare every configuration manually? (No way — maybe for 10,000+ devices?!)


OK, let’s step back. Here’s how it usually goes:

  1. Gather and analyze all requirements
  2. Define the needed solutions
  3. Prepare configurations
  4. Plan deployment and coordinate across multiple parties

So the question is: what can AI help with?

I asked ChatGPT about step 3 — configuration preparation and the best automation method.
It gave me this:

Use Case                  | Best Tool
--------------------------|--------------------------
First-time provisioning | 🟠 ZTP
Day-2 config, updates | 🟢 Ansible
Dynamic runtime scripting | 🔵 Python

You don’t have to choose just one — combining them leads to full end-to-end automation.

Great! But… what about the rest of the steps to complete a full solution?
Can AI help us with the entire plan?

I think this is how you should approach it:

  1. Analyze the requirements in detail
  2. Identify what the solution needs
  3. Prepare the configurations
  4. Design the deployment plan

You’d need to provide AI with a comprehensive scope of work, and then ask it to generate a plan.


But can you trust it?

YOU need to verify all outputs from AI.
YOU need to plan the project timeline and human resources.
YOU need to review the configurations generated by AI carefully.

If you don’t know networking, project planning, or resource management — how would you even do that?

That’s why:
YOU = Network Engineer, Network Project Manager

We’re always learning new things. AI is becoming a great assistant, but right now, we shouldn’t fully trust it without verification.


As I said before:
Can AI operate the Internet?
Well… that depends on how the AI is designed to manage networks, and which parts of the network it’s capable of operating.

Discussion continues…

AI Network Operator – under Deepseek case

We all know how successful Deepseek has been in recent months. It demonstrates that a low-processing-power, CPU-based AI is possible. Adopting this type of AI anywhere, including IoT devices or even routers, could be feasible.

Cisco, Juniper, Arista, and other network device manufacturers already produce hardware with high processing power. Some of these devices run Linux- or Unix-based platforms, allowing libraries and packages to be installed on the system. If that’s the case, can AI run on them?

Based on Deepseek’s case, tests have shown that an ARM Linux-based Raspberry Pi can successfully run AI. Although the response time may not meet business requirements, it still functions.

Running AI on a router (perhaps within the control plane?) could enable AI to control and modify router configurations. (Skynet? Terminator?) But then, would the AI become uncontrollable?

There are several key questions to consider:

  1. What can AI do on routers and firewall devices?
  2. Can AI self-learn the network environment and take further control?
  3. Can AI troubleshoot operational issues?

It seems like an interesting topic for further research. However, before diving deeper, teaching AI about network operations should no longer be a major concern.

Paragraph proofreading by #ChatGPT

AI Picture generated by #CANVA

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