A Look Into the Future with Futurist Kevin Surace

Estimated reading time: 14 minutes

Futurist Kevin Surace might have been great as a writer for science fiction TV and movies where technology was just within the realm of imagination and great camera tricks, but he’s actually spent his career learning and inventing technology in real life.

In this interview after his keynote address at IPC APEX EXPO 2025, Kevin reflects on important lessons learned and how they shaped his own future. He also makes some bold predictions for the use of AI in PCB board design, fabrication, and assembly—and what the common household will look like in 10 years. It’s an exciting and adventurous step into a future where humans work alongside robots, all for the betterment of everyone.

Barry Matties: Kevin, thank you for sitting down with me today. I was really inspired by your keynote. I’m wondering who inspired you in your life?

Kevin Surace: You learn from so many people. My dad was a fantastic leader. He was a manager at General Electric, and that's probably why I sided with electronics because we had them around the house where I could take them apart, fix them, and make them better.

I’ve also had a variety of bosses that I’ve learned from. Some you want to be like; others you learn you don’t want to be that kind of boss. But I was inspired by all of them. I learned things that really worked well for me, and other things that I shouldn't do.

When I was 18, I worked retail for Sounds Great, an audio/visual space company in Syracuse, New York. I was the video and computer manager, but also worked sales, because everybody's in sales when you’re on the floor, and my sales numbers were great. One time, a sales trainer gave us this amazing sales training based on the Dale Carnegie sales course. I flunked it. My manager pulled me aside and said, “You’re the best sales guy in the store and you're one of the top 10 in the company, but you probably could have been number one if you had paid attention instead of thinking that you know it all.”

So, the next time they came through, I paid attention. I did well and then I became the course trainer. I learned that no matter how good you are, you still need a coach because they see things you don't.

Over time, I’ve also realized that we all think IQ will get us to the top. Well, good luck with that. There's a lot of IQ out there, and I probably won’t be smarter than everyone. It will never happen. But I can learn how to listen better and how to interact with people, and build out my EQ. That’s what will take you the furthest. You need to learn some other skills.

Matties: You’ve been well recognized with awards and achievements over your storied career. What were some of your defining moments?

Surace: There are probably a hundred of them. One time, I took a bit of a break from electronics and software to focus on clean tech. I found that the “built” environment all up—including building and retrofitting our buildings, heating, cooling, and lighting our buildings—was about 53% of all CO2. Now, how can that be, because our buildings don't generate anything?

While that’s true, the power plant down the street does and it all goes to your buildings. It's not going to your cars. It was a serious issue, and I wanted to see what I could do to reduce heat loss, lighting, and HVAC. How could we control it better and use AI to understand how we can reduce the energy in our buildings?

I was coming up with many new kinds of materials. I'm not a material scientist, but I had some ideas. I said, “Can I learn enough about this?” I’d had an idea about constrained layer damping and how it could work, but no one had ever applied it to drywall. It's this physics thing that happens. 

I had to learn so much about this. You can never go to college and spend half a year just on a constrained layer-damping system. That’s ridiculous. I spent weeks reading every patent and claim I could find, none of which had to do with drywall until I thought, “I am really smart in a tiny little area that absolutely no one in the world probably cares about.,” It was a learning moment for me because while I couldn’t be smart at everything, I could get really good at this one tiny little sliver. From that learning, I invented soundproof drywall called “Quiet Rock.”It’s a huge, billion-dollar product line now used in every hotel, condominium, and townhome.

I learned how to take that sliver of genius and potentially make drywall that does this. That was fascinating, and I learned a lot from that experience.

Matties: Perhaps not being locked in by the paradigm is the best approach.

Surace: It was the best approach because the drywall business said, “You'll never be able to do that. We've had a hundred years to do it, and no one's ever done it.” My reply was, “I think no one ever tried, so I don't know that it can't be done. Rules are there for followers.”

Matties: Thinking about the effort you put into Quiet Rock, if AI had been available then, how might that have changed things?

Surace: Oh, that's interesting. I would have asked a GPT-4 reasoning model, “Here's my problem. This is what I know and what I don't know. This is what I'm solving, so give me some ideas on where to look and how I might go about it.”

When I did the research, there was no book to consult, no one to talk to. It was impossible to find such information. If I did it now, I would ask the models how to solve the following problem and use these models as idea generators. All the ideas are not right, but they're better ideas than you had a minute ago. 

Matties: Let's connect that to circuit board design. A lot of people say AI will never replace the circuit designer, but I'm of the mind that the board will never be better than what AI will ultimately produce. 

Surace: Remember that AI has learned millions of circuit designs, by chance, because they're out there to be found. It won’t be perfect, but humans aren’t perfect either. When you design a PC board, you make a lot of errors, go back and forth, and move components around. You might say, “I don't have room for this clock line or this power line, these lines are too close, it will be too noisy,” or whatever the case is.

It's trial and error. You work on it and work on it, and then you prototype it, and you find that you still might have to move a couple of things around or isolate something. This is what we do. AI will do a better job than you, but you will be in charge of the AI. You still get to edit, change, and agree or disagree with it. But in five minutes, AI PCB layout and routing will blow away what any human can do in five days. Now you’ve saved the rest of those five days. You're off to prototyping, making a few edits, and off you go.

So, of course we will use these tools. Think about large chips, especially microprocessors and GPUs, that have not been laid out by humans for a very, very, very long time because there are billions of transistors. It's impossible. In 18 layers, it's not possible for a human to contribute much to that. Now, we still oversee it, but we've been the robot overlord of that kind of place-and-route for decades. We had no choice but to go to machines.

Let’s look at another example—the eye surgery known as LASIK. Most people don't realize it operates itself: The doctor pushes the start button and that's it. But they couldn't get FDA approval because it needed to have optical sensors that ensure you don’t move your eye. If you move your eye, it'll slice up your cornea. So, if the eye moves, the laser stops immediately by itself. It is a fully automated surgical device that's been around for 40-plus years. It’s highly trusted, and does a great job. But there are now AI versions that are even much better. No human could have done that work. We would have sliced up people's corneas because we can't respond fast enough. 

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