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Hardware is the New Salt: How AI Helps Democratize Innovation in Hardware Design and Manufacturing

Editor’s Note: This essay is part of a new series exploring how AI is transforming the way physical products are imagined, designed, and built. Hardware is the New Salt will spotlight several thinkers and makers at the intersection of AI and product design and their insights into this dynamic technology ecosystem. This series is supported by Enzzo, who offers an AI-first product development platform created to support the next generation of builders.

Decades of physical product development now intersect with cloud connectivity, AI, and advanced computing, marking a shift in the way we design hardware. In the past, devices like Sony Handycams or Casio organizers stood on their own, disconnected and limited in their scope. Today, a fusion of intelligence and context powered by IoT, powerful chipsets and machine learning models are accelerating innovation at scale.

This moment is about speed, not just of computing, but of experimentation and iteration. AI allows us to compress what once took six months into six days. At Fluke, during the discovery phase, we’re using tools like Enzzo to quickly mine customer insights, build personas, model value propositions, and simulate bill-of-materials, at pace. That acceleration allows us to play faster, test ideas more rapidly, and refine more precisely.

When we move into the delivery phase, AI helps bridge the historically conflicting models of hardware’s waterfall approach and software’s agile processes. From prototyping to firmware to rendering, AI-driven tools enable faster iteration across physical and digital boundaries. Then comes the sustain phase, where products are in-market and generating data. AI is changing how we ask questions about usage, performance, and customer behavior. No longer limited by dashboards or SQL skills, teams can now pose natural language queries and get answers in seconds. That’s a revolution in operational intelligence, and a lever for continuous improvement.

However, what makes this generation of technology different from past shifts is not just power or capability, it’s usability. With natural language interfaces, you no longer need to write code to be productive; you just need curiosity. That radically lowers the barrier to adoption, speeding up learning curves across entire organizations.

But speed isn’t without risk. We take that trade-off seriously at Fluke, where safety and precision are paramount. There’s a line we won’t cross with generative AI. While we’re happy to use it for product recommendations or visual renderings, we never deploy it where safety or compliance is on the line. There is an ethical responsibility tied to innovation, one that pushes barriers but never jeopardizes the intention of designing in the first place. With this at the forefront, our cycle of innovation prioritizes trust and human capacity, keeping a check on AI, its applications, and results.

This is where democratization comes in. For innovation to grow within any organization – there must be increased access to design tools, software, and training across departments. We’ve seen repeatedly that passion and curiosity can trump credentials. The ability to experiment, test, and iterate is innately human. AI enables more people to try, fail, learn, and eventually build meaningful things. That’s how innovation should work.

Hardware has always been difficult; long lead times, complex integrations, and in some cases, expensive mistakes. But AI can help flatten that curve, giving us faster feedback loops and more dynamic product-market fit testing. At the same time, it rebalances the power dynamic between software and hardware. Hardware has been commoditized by software for years. Now, as AI commodifies software, the spotlight turns back to hardware as the irreplaceable interface to human experience.

It’s this that also led me to return to hardware after years in cloud computing. Every interaction, whether with a device, a tool, or a service, ends in the physical world. You can’t feel, touch, or experience software without hardware. The magic happens at that intersection.

Still, trust doesn’t happen overnight. It’s our job to educate and show the art of the possible with AI, so we host AI demo days, lunch-and-learns, and summit events to expose our teams to different use cases. More importantly, we explore what’s possible when you can use AI responsibly in an environment where you are free to try and test, before scaling. [GM2]

Ultimately, this is about responsible acceleration. By giving people the tools and guidance, we can create environments where people are free to explore without setting them up to fail.

AI is still in its infancy, but its learning curve is exponential. Our responsibility is to guide it carefully, while it’s still learning to walk, as one day we’ll need to trust it to run.

About the author:
Vineet Thuvara is the Chief Product Officer at Fluke Corporation, one of world’s leading companies in test and measurement devices, software, and services. In his role he leads the Fluke business units and is responsible for growth, new product innovation and strategy apart from being a champion for AI. Prior to Fluke he was General Manager and Director at Amazon, leading the Echo product organization responsible for developing and shipping Amazon’s First-party Alexa based AI devices and experiences.

Before joining Amazon in 2021, Vineet spent 15 years at Microsoft in various leadership roles across Surface, Xbox, and Server and Cloud product organizations. Prior to that he was the co-founder and CEO of 5th Quadrant, an Industrial Design company based out of New Delhi, India.

Vineet holds a Bachelor of Technology in Mechanical Engineering from University of Calicut, MS in Industrial Design from Indian Institute of Technology Delhi, and an MS in Engineering and Management from the Massachusetts Institute of Technology, USA. He is co-author of the Life-Cycle Engineering Handbook for Indian Industries, guest lecturer at multiple universities, product advisor for start-ups, holds several patents, and has held scholarships at the Delft University, Netherlands and Hitachi Design Center, Japan.

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