The rise of AI in recent times has been one of the most controversial topics around the globe. Some call it a threat, others see it as the way forward. Technically, there are many kinds of AI, each performing different functions: generative text AI, image AI, audio and music AI, video AI, browsing assistants, AI for entertainment, and more. But the debate remains: is this growing trend truly a positive phenomenon? In my opinion, there is no such thing as a good or bad tool- only good or bad use of it.

Industrial design is one of those fields where even the simplest details can take significant effort to visualize using traditional tools. That’s why designers spend so much time mastering the skills and software we need to communicate our ideas effectively.

This raises an important question: how much effort is appropriate at what stage of the design process? For example, during initial client presentations, designers often prepare multiple concept options to help clients choose a direction. Nothing conveys intent quite like a polished model or a detailed render, but is the effort worth it when there's always a chance that none of the options are selected or at most one is?

Perhaps... AI can help…?

In this context, AI is a speed booster, not a shortcut. Industrial design involves a wide range of tasks, from rough ideation and early sketches to photorealistic renders and prototyping. Many of these tasks are repetitive and time-consuming, especially in the exploratory phase. AI tools can help by generating quick variations of forms, concepts, and visuals, enabling designers to present more ideas with less manual effort. This shift frees us to focus more on strategic thinking, user needs, and creative decision-making.

Sounds like a dream, doesn’t it? Well, there’s a catch.

While AI offers speed and creative support, the reality of using it can be more complex than it seems. Getting desirable results often involves tedious trial and error: writing and refining prompts, sifting through unusable outputs, and manually adjusting assets. AI lacks contextual awareness, making it prone to producing designs that are unfeasible, ergonomically flawed, or culturally off-base. Outputs can be inconsistent, and integrating AI results into professional CAD workflows often requires time-consuming rework. There’s also the risk of creative detachment; without strong direction from the designer, AI can generate generic or soulless outcomes. Add to that the ongoing ethical concerns around authorship, copyright, and the steep learning curve. 

it’s clear that AI isn’t effortless; it’s just a different kind of effort.

In conclusion, I’ll say that AI must be used for co-creation with both parties learning and growing along the way. With AI taking over repetitive execution, the designer can evolve into a curator, strategist, and visionary; someone who brings intent, empathy, and meaning to the table.

Ultimately, the designer’s thinking becomes the true differentiator.