Design, Disruption, and an AI Blueprint for Growth
Article
Featuring
Kenny Tai
Share
In every era of product development, there are a few breakthroughs that redefine the rules—moments when the tools change so dramatically that the winners aren’t the ones with the most resources, but the ones who adapt fastest. We’ve seen it with the internet, with 3D printing, and with the rise of global supply chains. Now, artificial intelligence is bringing another of those inflection points, collapsing timelines, stripping away inefficiencies, and rewriting what’s possible for teams of any size. The question is no longer if AI will shape your business—it’s whether you’ll be a leader who is ready when it does.
When I was 26, I pooled savings with my roommate and a few friends and took a gamble. We dove into trading, sourcing products from China, and even flying halfway around the world to meet factories that would produce our products in person. There was significant fragmentation in the product creation process; this was a barrier we were determined to overcome. Having been born in Taiwan and being conversational in Mandarin, I still found working with manufacturers difficult—a realization that if it was hard for me, it must be even harder for entrepreneurs with no language skills at all. Though critical, there were other challenges.
"Now, artificial intelligence is bringing another of those inflection points, collapsing timelines, stripping away inefficiencies, and rewriting what’s possible for teams of any size. The question is no longer if AI will shape your business—it’s whether you’ll be a leader who is ready when it does."
The U.S.-based design agencies I used didn’t solve the problem. They produced beautiful concepts, but they left clients stranded before mass production, still facing the tangle of negotiations, quality control, and finding the right partner. By 2008, I decided to close the gap myself. I moved to China, offering design, sourcing, and manufacturing services for non-Chinese speakers. Three years later, with investor backing, I founded Gizmospring, complete with its very own factory. Finally, I was able to put the whole process under one roof.
Now, the conversation in hardware design is all about artificial intelligence—and I believe it’s a generational shift, not a passing trend. AI can erase the endless back-and-forth that drags product development, compressing the time from idea to market-ready. But it demands more than new software; it requires a new mindset.
The opportunity is clear: hand off the tedious, repetitive work to AI—such as status updates, early design iterations, and first-pass quality checks—and reclaim human energy for strategic decisions, creative refinement, and solving problems that machines can’t. Resisting that shift is a dead end; mastering it is where the advantage lies.
I practice what I preach—constantly reading, taking courses, and experimenting with tools, then sharing what I learn. One of my business development leaders has become our AI scout, testing applications for integration. I envision a permanent experimentation team embedded in the company, a continuous learning engine to stay ahead of the curve.
"The opportunity is clear: hand off the tedious, repetitive work to AI—such as status updates, early design iterations, and first-pass quality checks—and reclaim human energy for strategic decisions, creative refinement, and solving problems that machines can’t."
My ambitions match my pace. In ten years, I want tenfold revenue growth with a slightly smaller team. In the AI era, even single-person unicorn companies will be possible. I’ve seen significant shifts before—3D printing, which transformed prototyping, and Zoom and Skype, which rewrote the rules of collaboration. But AI, to me, is more like the arrival of the internet: a structural change that will decide winners and losers. This time, the skills gap between early adopters and holdouts will be a decisive factor.
I know adoption won’t be flawless. Mistakes will happen. I avoid feeding sensitive intellectual property into AI systems and set clear limits on what the tools can access. Trust is built on discipline—use AI for the safe parts of the workflow, but keep humans in the loop where judgment matters most.
It’s a simple equation: let AI take the work people don’t want, and embrace the creative, strategic, and ethical challenges that remain. The companies willing to do both will own the next decade.
Kenny Tai
Founder, CEO at Gizmospring
