AI is everywhere. In design, there’s some fear it might be coming for our jobs. Headlines make it sound like either the next big thing or the end of humanity – but the reality is, as always, more nuanced.
Already, when searching for images, music, videos, or books, we’re being flooded with AI-generated dross. It’s often low quality, churned out to cash in on platforms that let creators earn a little revenue. Ironically, the returns are so small that an AI scattergun approach might be the only way for creators to make it viable.
AI is still just a tool, and that’s how I approach it – with curiousity, hoping it might speed up parts of my process. Recently, I was stuck on a tricky design problem and my team was already stretched, so I asked ChatGPT for some UI pattern ideas. It shifted me out of the mental model I’d built and offered a fresh perspective. I could then see how valuable this would be for those solo unicorns working in a design team of one.
I like how AI can cut through complexity and generate options. We’re also exploring whether it can fast-track turning the Design System we’ve built in Figma into code. Having built a Design System from the ground up, I can tell you even a small team faces a mountain of work. We’ve been refining our Figma library for years, and the design decisions feel solid, but translating it into code has always been the hard part and now its so big it sometimes feels impossible.
I’m old enough to remember hacking Dreamweaver to make it write code properly, so I’ve never had much faith in “generated code.” But now, with the right framework, AI can produce surprisingly solid code incredibly quickly. You still need an expert to review, refine, and set up the system, but the time saved can be measured in months. We’re in a skill-shift era: knowing how to get the right output from AI will make life a lot easier – much like those days when asking Google the right question gave you superpowers.
AI learns from existing systems. It can cut through complexity, but it does so by looking for patterns – and in doing so, often compounds systemic issues. It reinforces biases, sticks to creative safe zones, and can repeat accessibility problems present in the status quo. That’s why humans must remain central to the design process: to guide decisions, inject creativity, and uphold ethical standards. At the same time, AI can make design more accessible and raise the baseline across the board, leaving the most interesting, complex challenges for humans to tackle.
In the end, AI isn’t here to replace us – it’s here to challenge us to work smarter, not harder. It can speed up the mundane, spark new ideas, and even raise the baseline of design and code. But the magic – the creativity, empathy, and ethical choices – still come from humans. AI might hand us the tools, but it’s up to us to build something meaningful with them.