By Florian Weiss, Founder & Senior Business Management Consultant - Steps-to-Excellence, Germany
A look beyond the hype
The design world is transforming profoundly. Our social media feeds are now full of AI-generated images, blurring the lines between human creativity and artificial intelligence. This is not just a trend. It indicates major changes in the design field. The developments paint a picture of both excitement and apprehension. Amidst these uncertainties, one thing remains clear: the inevitability of businesses embracing AI as a cost- and time-effective solution.
AI tools advance rapidly, with updated news on a weekly base. Designers need to keep up and innovate. They must understand how their roles are changing due to AI. This article explores how generative AI is reshaping design. Time to look beyond ChatGPT, Midjourney, and co.
The Rise of The Silent Designer
People without proper design education have always influenced or made decisions on design. However, with the advent of AI, the phenomenon of silent designers has gained momentum, enabling individuals from diverse backgrounds to create visuals with minimal technical expertise. From social media marketing to small businesses, AI-powered design tools are revolutionizing content creation and distribution, democratizing access to design resources like never before. With increased productivity and better tools, there is a risk of saturating the market with acceptable—but not exceptional—design work. This proliferation of amateur designers could potentially exert price pressure on some design services.
Adobe’s GenStudio is taking advantage of this, it is a generative AI product, that lets marketing teams quickly plan, create, manage, activate across apps, channels, and publishers, and measure on-brand content. It streamlines and enhances the end-to-end content supply chain, covering planning, creation, production, asset management, delivering, insights and reporting. This allows personalized content delivery on scale, while lowering the required competencies needed to design and share content.
As AI takes on more mundane tasks, designers are allowed to focus on higher-level creative tasks. Figma's VP of design says AI "lowers the floor and raises the ceilings." This means AI makes design easier for beginners and creates new possibilities for experts.
The AI control problem: From features to workflow
Despite its potential, the current state of generative AI lacks the level of control that designers are accustomed to in their traditional design software. Control of the outcome is the main topic of recent feature updates. Techniques such as inpainting, outpainting, upscaling, style consistency, style-shifting, custom style generators, relighting, layer diffusion, structure reference, and character reference are already providing designers with some influence over their creations. These are useful features, e.g., for the creation of product staging, user journeys, or storyboards. The rapid improvements of new features are promising to make genAI a powerful tool for designers. However, this also means it will soon require as much competence as with traditional design tools to master the control of the outcome. Interesting here is the work of Martin Nebelong, who explores the frontiers of 3D sculpting with AI.
Notable applications & explorations:
Product staging in Midjourney and CREF with objects by Rory Flinn
Workflow with Stable Diffusion and ComfyUI by Leonardo Cunha
Beeble SwitchLight
SD forge layer diffusion on Github
ComfyUI Phtoshop plugin htps://m.youtube.com/@AI.Mind Merge/videos
3Dsculpt to render and Magnific Render by Martin Nebelong
Adobe is yet a bit behind; while taking a more conservative and compliant approach (even after their Max 2024 conference). They are slowly integrating similar features, e.g., generative fill, gingerbread, structure reference, etc. and neatly integrating it into all their 2D, motion, and 3D software. A great overview, evaluation, and comparison of AI-enhanced software tools for designers and design researchers was done by Allovus.
Let us go from features to workflow: To integrate AI seamlessly and keep control over the outcomes, a combination of diverse tools is yet required. Explorations into this realm involve leveraging traditional design software and various generative AI tools such as Krea, Midjourney, Vizcom, Magnific, Runway, and Beeble, alongside real-life interaction approaches like look-through windows and screen capture (see the box for some great examples). Three notable sources offer insights into incorporating AI into design workflows:
Experimentation with AI-driven design workflows and adoption of AI-powered tools and platforms are crucial steps for designers. The future promises the integration of these disparate tools into unified full-stack software solutions or suites. Already today, generative AI design tools have a high complexity if you aim to master control over the outcome. To deliver high-quality work specialized knowledge and competencies will be needed. This is an opportunity for the AI-enhanced designer. By embracing AI as a co-worker, designers can unlock new opportunities for collaboration and enhance efficiency in the design process. As AI tools become more embedded in the design process, they redefine collaborative roles: developers increasingly influence design decisions, and designers are taking on more strategic roles. The potential for AI to act not only as a tool but as a collaborator is beginning to reshape the creative industry.
As the intersection of design and coding deepens, the accessibility of creating functional interfaces grows, thanks to more user-friendly design systems. Andrew Hogan of Figma notes, "As design systems become easier to use and more widely accepted, more people can create passable interfaces. However, there is a growing demand for not only great but also novel interactions. Companies are eager to stand out, and this desire for differentiation increases the demand for skilled designers."
New avenues in industrial design and architecture
Another big player in the design software industry is Autodesk. Autodesk, in contrast, leverages its long history in engineering and architectural software to introduce AI into more complex, computation-heavy design tasks. This includes using AI for simulation, predictive analytics, and material optimization, all crucial for large-scale projects. Autodesk’s approach integrates AI tools to improve accuracy and efficiency in the creation of detailed engineering plans and architectural renderings, thus broadening the scope of what can be designed and built with precision. Especially, the merging of AI with generative design has huge potential for generating novel solutions. Generative design (not to be confused with Generative AI) is a design method that uses algorithms to generate a wide range of potential solutions to a design problem based on specified constraints and goals.
Key findings: The Impact of AI on Design
As we look to the future, the intersection of AI and design promises to enhance how we conceive, plan, and execute projects across various industries and design professions. This transformation, while still in its early stages, signals a significant shift in the creative industry, one that all stakeholders should be prepared to engage with as we move forward. The integration of AI into the design process is reshaping roles, workflows, and creative outputs in profound ways. Here are some of the key findings from the exploration of AI in design:
While we have touched on the profound transformations AI is bringing to design, from reshaping roles and workflows to enhancing creative outputs, we have only scratched the surface of what is happening in the expansive field of generative AI. An exciting future for designers lies ahead if we proactively utilize and shape how we use AI in design.
