AI Image Generation for Network Diagrams: My Insights

As network engineers, we spend a surprising amount of time creating diagrams. Whether it is for documentation, client presentations, or internal runbooks, a clear visual can save hours of explanation. So when AI image generation tools started maturing, I wanted to find out: can they actually help us build better network diagrams faster?

The short answer is: sometimes yes, sometimes no. Let me walk you through what I have found after experimenting with several tools.

What AI Image Generation Can and Cannot Do for Network Diagrams

AI image generation tools like DALL-E 3, Midjourney, and Adobe Firefly are exceptional at producing visually polished, stylized graphics. If you need a compelling hero image for a presentation slide, a conceptual illustration of a cloud architecture, or a diagram for a blog post thumbnail, these tools deliver quickly.

Where they struggle is with precision. Network diagrams require accurate topology representation, consistent iconography (routers, switches, firewalls), and correctly labeled interfaces. Current text-to-image AI tools are not built for this level of technical specificity. You will often get visually interesting results that are technically meaningless.

Here is a practical breakdown of what works and what does not:

• Works well: Conceptual cloud diagrams, architectural overviews, presentation visuals, blog post graphics
• Works poorly: Precise Layer 2/Layer 3 topologies, labeled interface diagrams, protocol-specific flow charts

The Better Approach: AI-Assisted Diagramming Tools

Instead of pure AI image generation, the tools that are genuinely useful for network engineers combine AI with structured diagramming. Here are three worth knowing:

1. Eraser.io

Eraser (available at eraser.io) lets you describe your architecture in plain text or a simple diagram-as-code syntax, and it generates a clean diagram automatically. It handles cloud architecture diagrams and network topologies reasonably well. The AI chat feature can help you refine or expand a diagram from a written description.

2. ChatGPT with Mermaid or Draw.io XML

This is my personal favorite workflow. You prompt ChatGPT to generate diagram code rather than an image. For example, you can ask it to produce a Mermaid.js network diagram or an XML file that imports directly into draw.io. The result is a structured, editable, technically accurate diagram.

Here is an example prompt you can use in ChatGPT:

Generate a Mermaid diagram showing a simple three-tier network:
- Internet router connecting to a firewall
- Firewall connecting to a core switch
- Core switch connecting to access switches in two VLANs (VLAN 10 and VLAN 20)
Label each connection with relevant interface names.

ChatGPT will return Mermaid code you can paste directly into mermaid.live to render the diagram. From there, export it as an SVG or PNG for your documentation.

3. Microsoft Copilot in Visio

If your organization already uses Microsoft 365, Copilot in Visio is worth exploring. You can describe what you need in natural language, and Copilot generates a starting diagram using Visio's native shape library. This keeps your diagrams consistent with standard network iconography, which matters for professional documentation.

Practical Tips for Getting Better Results

• Be specific in your prompts: Vague inputs produce vague outputs. Specify device types, connection types, and VLAN or subnet information upfront.
• Use AI for structure, humans for polish: Let AI generate the skeleton of the diagram, then refine it manually in draw.io or Visio.
• Generate in code, not pixels: Mermaid, PlantUML, and Draw.io XML are far more useful outputs than raster images when precision matters.
• Use DALL-E or Midjourney for presentation graphics only: Save pure AI image generation for slides, blog thumbnails, and conceptual visuals where artistic quality matters more than technical accuracy.

My Honest Assessment

AI image generation is a genuinely useful addition to an IT professional's toolkit, but only when you match the right tool to the right task. For polished visuals, DALL-E 3 and Midjourney are impressive. For accurate network diagrams, your best bet is a combination of ChatGPT for code generation and a dedicated diagramming tool for rendering and editing.

The engineers who benefit most from these AI tools are not the ones trying to replace their workflow entirely. They are the ones using AI to eliminate the blank-canvas problem and speed up the first draft.

What's Next

Now that you have a sense of how AI image generation fits into network documentation, the next logical step is exploring how AI can help with written documentation, specifically generating runbooks, configuration summaries, and change request templates from CLI output. We will cover that in the next post.