The Role of AI Image Generators in Modern Design

AI image generators are a concept we had hardly heard of just a few years ago. From piecing together pre-made components on Canva, we very quickly reached a point where we can prompt a design idea in plain English.

These tools use algorithms to interpret a user's prompt and generate a corresponding visual output. In many ways, it is worth learning about the math and machine learning behind it to some extent, because it can inform us of its limitations and biases. It can also remind us of just how far we have come.

Previously confined to research labs, they're now available to the public and for less than a Netflix subscription. This has posed an existential threat to designers - but is it really one? Or is it just another tool in their arsenal?

AI in Creative Industries

Artificial intelligence has dabbled in art for years, but with essentially no yield. It is only since the DALL-E became popularized that things changed, and the everyday person had access to professional-looking images that didn’t exist on the internet.

Diffusion models for example generate images by gradually adding and removing noise, while  Generative Adversarial Networks (also known as GANs) use two competing neural networks to refine the image quality. 

Accessibility

The major advancement over the past year has been the improvements in efficiency, meaning that better images can be generated with less energy. Ultimately, this is what is keeping the cost down, and it’s why there’s little market for high-end, commercial-grade expensive image generators. The same goes for a typical AI video generator, which is similarly affordable - though the limitations feels greater, in that the videos are often short.

AI Generators are Impacting Design Workflows

Both AI image generators and video generators have mostly been used for photorealistic images, anime, memes, and cartoon creation. In other words, the image has mostly been the art itself, rather than an element within design.

The exception here has been with stock imagery, which will likely be an industry facing an existential threat, as well as abstract imagery for web designers. These can be truly unique and generated in an instant - something the reader will have never seen before.

However, this isn’t to say that AI image generation cannot be used for design, such as creating components, shapes, and banners. It’s just that we are still jumping from text prompt straight to the end result. While many tools do allow for tweaks to the model (such as temperature), the user still goes from input to output in one swoop. This is fast, but the downside is the difficulty in iterating on a single image. 

For example, if you like what it produced, but you want to alter its ratios and color scheme - amending a prompt and generating a new image may result in something totally different. This makes it hard to be a part of a refined design process for logos, banners, and other graphical elements, but isn’t so much a problem for stock imagery and photorealism.

Efficiency Gains

It’s not just the AI models that have gotten more efficient. The result has been that prototyping and mock-ups have benefited. Instead of time-consuming manual creation, designers can rapidly generate visual prototypes for website layouts and product concepts. This speeds up the initial design process greatly, and makes the iterative limitations less of an issue. 

The exploration of unusual materials and visual styles is now far simpler. AI tools allow designers to test textures patterns and color combinations that would otherwise be complex or lengthy to produce. Before, it may take a while to generate a single mock-up for a client. Today, we can present them 5 different mock-ups, each with a different AI generated design elements, in the same amount of time. The result is the client choosing which of the 5 they like the most, feedback on what to change, and the final design can still be quite hands-on.

Content creation is ultimately streamlined, and so too is the copy. Plus, the way clients make requests is in their own plain language communication - which is precisely what AI generators work with, so there is no technical translation error here. Now that workflow is sped up, designers can refocus on strategic planning.

Democratization of Design

The arrival of AI image generators is lowering barriers to design, and it’s allowing those without formal training to create sophisticated visuals. So, not only is it affordable, it’s accessible for those without technical training. Plus, no software capital is required, and most providers work on a subscription-based model. 

Therefore, small businesses can now produce their own professional-looking marketing materials, allowing designers to be in-house more. With the plain language prompts, it might be that the mock-ups are generated in-house for then a designer to use as a springboard - but that ultimately saves money, and it guides the designer with more information. 

It’s also a tool we are seeing a lot of on social media. There is a virality to many of the AI images and video, particularly when used in a comedic way. This presents an opportunity to junior designers to build an online presence, with the AI tools facilitating both more output and opportunities to be unique. After all, some of the videos that can be produced in minutes would take weeks of professional directing, hiring actors, and creating sets.

Final Word

AI image generators are having a strong impact on design, but it’s far from a story where humans are left out of the equation. Beyond being a tool to speed up workflow, it can be a way to guide freelancers and agencies to stay on-track with the client’s vision - as their vision can be expressed in plain English.