Here’s a simple chart I created comparing three ways AI is changing data visualization workflows:

1. AI-Painted visuals (OpenAI ImageGen, Google Imagen, etc.)

You provide the data and a prompt. AI (using Python/R behind the scenes) calculates everything, then literally paints the final visual—labels, annotations, shapes, images—all at once.

2. AI-Enhanced Coding (ChatGPT/Gemini + matplotlib, ggplot2, seaborn)

The familiar way, now AI-assisted. You prompt AI to generate data visualizations using standard coding libraries.

3. Hybrid Visualization Tools (MyLens, napkin, Gamma, etc.)

New AI tools specifically built for visuals/graphs/charts. They analyze your data (structured or unstructured) and quickly create visuals. Some with more focus on understanding complex data and interactivity (mylens ai) and some with more focus on design and layouts (napkin ai and gamma app)

Tools used: MyLens ai for visual, categories based on my experience.
Not actual usage data, more of a qualitative framework to compare trends.

Would love to hear how others are using these tools or seeing this space evolve!