Design x AI: Clutch or Crutch?
Updated 07.08.2025 – added reference to MIT study
Every day it seems another AI tool is being rolled out – claiming it will reimagine the future of design. And with it, comes a spectrum of responses— some energetic excitement and wonderment, others with fear-mongering rants about how all designers will be out of their jobs in the next few months—they can’t all be right.
Vizcom AI promotional video
How do designers stay relevant in a market increasingly adopting AI capabilities?
The way I see it, there are two different camps: those who drive AI tools, and those who are driven by AI tools.
If you’re a designer who learned how to design products from the ground up, then you have the appropriate context and point of view to utilize AI tools because you understand what end you are driving toward and can recognize both the benefits that AI can enable, as well as its inherent limitations. Conversely, if you’re a designer who never truly learned how to design, then you’ll find yourself asking AI to fill in the gaps, and while you may get to an outcome through that path, it most likely won’t be the one you intended. And if you can’t communicate your intention, you are more likely to follow the path of least resistance and settle for the outcomes that AI presents to you, which by definition— is not design at all.
HOW CAN DESIGNERS BETTER UTILIZE AI TOOLS?
As designers, we are trained to visually communicate. But with AI tools, there is a need for clarity of verbal and written communciation as well. Designers must learn to communicate their intention more completely. Along with key visual communication skills, learn how to write with clarity. It’s also critical to understand the historical context of technology adoption to understand what language learning models (LLMs) are doing to shift the AI adoption landscape.
Early computers were specialized scientific equipment
HISTORICAL TECHNOLOGY ADOPTION
In the early days of digital technology, computers were considered scientific tools that only technically trained individuals knew how to use. Then the personal computer came along, which didn’t require advanced degrees in computer science to operate due to the advent of the graphical user interface (GUI). This paved the way for more people to engage with computing technologies. The GUI lowered the technical barriers to adoption, and made it more widely accessible. If you could understand the visual metaphors on the screen, (ie., a metaphor for a physical desktop), then you could use the technology to achieve a desired outcome.
Smartphone
Then the smartphone came along, and put the power of the personal computer combined with high-speed access to the internet in the palm of your hand— evolving the GUI interface into something that didn’t require a mouse and keyboard to use. This brought powerful technologies together at a massive scale, enabled by huge datacenters with vast networks of interconnected supercomputers. These powerful computing platforms generated troves and troves of data, which needed advanced algorithms to process and manage, giving rise to the AI models we use today.
OpenAI
To communicate with these advanced AI models, tech companies developed generative pre-trained transformers, or GPTs, to conversationally interface with these massive supercomputers. The advent of the GPT is the foundation of the language learning models (LLMs) we are seeing deployed at scale today in the likes of OpenAI’s ChatGPT, in Google’s Gemini, Tesla’s Grok, and too many others to mention. These LLMs are the next evolution in human-computer interaction, and they have once again lowered the barrier to adoption by reducing the engagement complexity to a mere conversation. We can just talk to the computers now.
Handcuffed by technology
DANGERS OF TECHNOLOGY DEPENDENCE
But with increasing capabilities comes increasing reliance on technology, all while we’ve conversely decreased our human capacity to learn. MIT studies are showing that exposure to AI technology too early in our human brain development is detrimental to our ability to learn, it negatively affects our attention levels, and decreases our mental health with continued use. Additionally, our over-reliance on technology reduces our critical thinking abilities by shortcutting pathways to the answers we seek– reducing the key cognitive challenges that our human brains crave, while simultaneously dulling our intrinsic drive to learn. As our human abilities to learn continue to wane, our dependence on technology will continue to increase as “cognitive debt” persists—cementing these mental shortcuts as permanent problem-solving pathways. This is bad enough for fully-developed brains to cope with, but it also signals a catastrophic danger to the developing brains of young children as these technologies are entering our orbit earlier and earlier in our youth.
HOW DESIGNERS CAN COMBAT OVER-RELIANCE ON AI
Master the Basics
Build a strong foundation in design principles is essential. These timeless elements empower designers to critically evaluate AI-generated suggestions and decide what truly resonates with the brand’s essence.
Engage with Traditional Methods
Sketching, hand-drawing, and physical prototyping foster a tactile understanding and intimate understanding of the problem you are looking to solve that AI cannot replicate.
Study Design History and Theory
Understanding the evolution of design movements and conceptual frameworks equips designers with a rich context. This knowledge guides thoughtful decision-making beyond immediate digital tools.
Experiment Beyond AI Outputs
Use AI as a tool, not a crutch. Challenge yourself to iterate designs independently or explore unexpected directions that AI might not suggest.
Collaborate and Seek Feedback
Human collaboration fosters diverse perspectives and constructive critique, which sharpens a designer’s perspective and prevents complacency within AI-generated norms.
Continuously Learn New Skills
Attend workshops, pursue courses, and participate in design communities. Continuous skill-building ensures adaptability and deepens creative capacity.
After half a century of learning how to think like a computer, it seems we need to relearn how to be human.
--
Jayson Simeon
Principal + Founder | Adaptitude
We design products, teams and capabilities that drive authenticity and brand momentum.