In this writing, I explore the use of Adobe Firefly, a creative generative AI model, as a color suggestion tool for building sequential color data schemes for your data visualizations. I do this by prompting the trained AI model for color schemes and then evaluate the results. Adobe Firefly is currently in Beta and its features are freely available upon applying and being accepted to their Beta access program. I will walk through the technical process, explain the color theory at work, and how to apply the selected color scheme to my five-step process of colorizing a data visualization, which I have highlighted in previous UX Collective and Nightingale writings. In data visualization, sequential color schemes are designed for ordering numeric information where colors progress from low to high (or vice versa).

Let’s begin by exploring some general details about what currently exists with Adobe Firefly.

What is Adobe Firefly:

Adobe Firefly is a beta software collection of Generative Artificially Intelligent (AI) models for building artistic content. The online version can provide creative images from text commands that you provide, referred to as prompts. Adobe requires that you apply to be part of the Adobe Firefly Beta program for online access. I was accepted in a few days, although others have noted longer time frames. Once accepted, you login by either creating an account or using your Google or Facebook credentials.

There are detailed reviews of the Adobe Firefly collection focused on creating generative artwork. One of the tools is a “Generative recolor” app that re-colorizes vector artwork from a text description. Below, I show an illustration of the Adobe Firefly interface and a detail of the “Generative recolor” tool.

In this writing, I am going to discuss how the “Generative recolor” app can be adapted to explore sequential color scheme options in your data visualizations. The first step is to convert an image from your data visualization work…