How Industrial Designers Can Find Their Footing in the Age of AIGC

Let me clarify upfront: this article is about AI tools like ChatGPT, Claude, Nano Banana, and Midjourney — not Adobe Illustrator, which also happens to have "AI" in its name. I wonder if Adobe had any idea, back when they named it, that this would one day become such an awkward coincidence. Ha.

AI development has been underway since the early twentieth century, but the generative AI tools that ordinary people can actually access and use have only really taken off in the last few years. The timing of their arrival in my life feels significant: 2021 to 2024 was the period I spent fully committed to my two master's degrees — driven by a hunger for knowledge, anxious about the job market, working hard but feeling more than a little lost.

Among creative industry professionals, attitudes toward AIGC tend to cluster toward two ends of a spectrum. On one end: beginners who pass off AI-generated images or text as their own work, convinced they've instantly leveled up to compete with seasoned professionals. On the other: practitioners with real skills and hard-won expertise who feel deep hostility toward AI-generated content — calling it "Frankenstein collage" or worse. That reaction is completely understandable, because the work these people spent years developing is very likely being scraped and fed into the models they resent. Who would want to watch their hard-earned craft get copied in a fraction of a second?

My own early relationship with AI was contradictory. I acknowledged that it could genuinely help me with things I wasn't particularly good at — like polishing my writing or handling practical life situations (the first time I experienced a break-in, it was actually AI that walked me through how to stay calm and deal with it). But when it came to my professional design skills, I kept AI at a skeptical distance. Early AI-generated images were riddled with errors; the text often contradicted itself. There was no stage in my workflow where I felt comfortable relying on it directly. And if I'm being really honest, I probably leaned toward one end of that spectrum myself: if everything I'd worked so hard to learn could be matched by someone using AI in an instant — what did all that effort actually mean?

Somewhere between late last year and early this year, I started encountering more mature AI tools and genuinely began integrating them into my workflow. I watched a lot of tutorials, listened to practitioners share their experience, and spent a solid stretch experimenting hands-on — and spending a fair amount on subscriptions. I've landed in a place that feels both optimistic and grounded. Here's what I've learned.

There's No Reason to Fear a Tool

Setting aside AI's ability to generate content from scratch based on a prompt, it is, at its core, still a tool. There's no good reason to fear being replaced by a tool — what you should be thinking about is whether someone who has mastered that tool will outperform you. Resistance, in other words, isn't the answer.

One piece of advice I kept hearing in tutorials stuck with me: give AI more time. Don't get discouraged after generating a few unsatisfying results. The landscape of AI tools is expanding rapidly, which means there's almost certainly one out there that suits how you work — and that choice will look different for everyone.

That said, people who use AI well will genuinely see significant efficiency gains, and that will reshape the job market over time. Work that once required a team of ten designers might now be handled by two senior designers working with AI. Many experienced practitioners are already worried about the disappearance of entry-level opportunities — the "missing apprentice" problem. But an efficiency-driven market will keep moving forward regardless. The most useful response is to get better at using the new tool.

The Key to Better Efficiency: Shore Up Your Weaknesses

AI's capabilities tend to be fairly broad rather than deeply specialized, which means its greatest value lies in filling the gaps in your own skill set. If you have an honest sense of where your weak points are, you can put AI to work precisely there.

Here's a concrete example from my own practice: I've never been particularly strong at compositing lifestyle renders in Photoshop. But Nano Banana can adjust lighting and perspective for me, and even generate a background image that fits my exact requirements from scratch. All I need is a well-constructed prompt — no more hours spent scrolling through Google Images looking for the right stock photo. What used to take hours now takes maybe fifteen minutes. Why fifteen minutes and not five? Because AI isn't always clever, and you'll often go through dozens of iterations to find one result that actually works. But even so, it's dramatically faster than before.

The output might not match what a Photoshop expert could produce — but it meaningfully improves my efficiency. The strategy I've settled on: assign the "grunt work" to AI, and keep the real thinking and decision-making for myself. At the end of the day, AI isn't the one walking up to present the work and being held accountable for it.

Maintain the Mindset and Habits of an Apprentice

AI can take a lot off your plate — but I still encourage everyone to put in the unglamorous work of foundational practice. I still sketch with markers regularly. Real intuition and judgment are built through repetition, day after day.

Someone using AI might be able to outpace a complete beginner. But taking shortcuts doesn't produce real growth. It produces work that looks increasingly like everyone else's — undifferentiated, lacking in originality. A creator with genuine foundational skill, a distinctive voice, and original ideas is still something AI simply cannot replicate.

Resisting the seductive ease of AI-assisted creation isn't simple. But for the sake of long-term development, the apprentice mindset has to stay. Let AI help you travel the road more smoothly — don't use it to skip the road entirely.

Think of Yourself as the Creative Director

I recently came across a joke: a team meeting is really just the manager doing vibe coding out loud. There's something to that. If you're frustrated that AI isn't producing what you want, think back to a time when you received a vague, unclear brief from a manager — you didn't know what they wanted, you did your best, and then got criticized for it anyway. AI is probably just as confused in those moments. The upside: AI never gets annoyed, and it never gets tired.

Your relationship with AI is like that of a creative director with taste and strategy, paired with a tireless but not-always-intuitive super-employee. This employee is capable of remarkable things — but they need you to be clear. Just as you wouldn't want to work for a manager who expects you to read their mind, AI needs explicit direction to do its best work. The more you refine how you give instructions, the more effectively you can unlock what it's capable of.

Always remember: you're the one doing the final selection and review. The output represents your taste. Without your ideas and clear direction, AI has nothing to work with. Being a diligent executor of repetitive tasks is not enough — taste and decision-making are your real competitive advantage.

AIGC Steps Worth Trying as an Industrial Designer

Some concrete suggestions for integrating AI into your workflow:

Secondary research: Use ChatGPT or Claude to help locate data and reports. Always verify accuracy and filter for what's actually useful.

Concept phase: Use Vizcom to quickly translate finished sketch linework into product renders — skipping the manual material rendering step and producing presentation-ready visuals much earlier in the process.

Rendering phase (product): Use Vizcom or Nano Banana to swap materials or refine surface treatments on existing renders — especially useful for effects that are difficult to achieve in KeyShot.

Rendering phase (lifestyle): Use Nano Banana to generate and composite scene backgrounds. Pay close attention to the scale and proportion of your product within the scene.

A note: I'd personally caution against using AI to generate design concepts during the ideation phase. It's easy to become dependent on whatever AI produces and let your own formal thinking atrophy. If you're confident you can manage that dependency, tools like Vizcom, DALL-E, or Midjourney can be useful for loosely exploring form directions — but be honest with yourself about how much you're actually thinking versus just accepting what the machine gives you.

If you're still skeptical or anxious about AI, I genuinely understand. My own relationship with it has gone through several distinct phases: initial shock, then doubt and resistance, then the frustration of trial and error, and finally arriving at something I'd describe as cautious optimism — using it thoughtfully without over-relying on it.

Design sits between art and technology. Embracing new tools has always been part of the discipline — some of the most celebrated design work in history was only possible because designers were willing to engage with the breakthrough technologies of their moment. AIGC is a powerful enough tool that social media is saturated with content designed to provoke anxiety about it. That's exactly why it's worth stepping back and engaging with it calmly and on your own terms.

You may not use it every day. But make sure it's in your toolkit — so that when the moment comes, and you need it, you're not scrambling to catch up.