Dave Evans, CEO and Co-Founder of Fictiv – Interview Series

Dave Evans, CEO and Co-Founder of Fictiv, leads the company’s mission to unlock the world’s creative potential by simplifying sourcing and the production of custom mechanical parts. With a background in hardware engineering and early experience at Ford’s Silicon Valley Innovation Lab, he co-founded Fictiv to streamline the hardware development process. Under his leadership, Fictiv has grown into a key player in the digital manufacturing space, producing millions of precision parts and driving innovation across industries.

Fictiv a global manufacturing and supply chain company that streamlines the production of custom mechanical parts through an integrated network of global partners.  Offering services like CNC machining, 3D printing, and injection molding, the platform combines instant quoting, AI-powered feedback, and end-to-end order management to simplify complex supply chains for engineers and manufacturers.

When you founded Fictiv in 2013, what was the core problem in manufacturing you were trying to solve, and how has that problem evolved over the past decade?

When my brother, Nate Evans, and I founded Fictiv in 2013, we wanted to break through manufacturing bottlenecks and build hardware at the speed of software. As a lead hardware engineer at Ford Motors, I saw firsthand how slow and painful it was to get custom parts manufactured—often waiting 8 to 12 weeks for prototypes, navigating fragmented supplier relationships, and juggling emails and spreadsheets just to get a quote. It was clear to me that if we wanted to accelerate innovation in hardware, we needed a better, more modern approach—one that mirrored the agility and speed of software development.

That problem hasn’t gone away—in fact, over the past decade, it’s only become more urgent as companies across industries push to innovate faster in a more volatile global market. What’s changed is the expectation: businesses now need to launch products faster, scale more flexibly, and respond in real time to shifts in demand, regulation, and supply availability.

That’s where the real power of a global, Fortune 500-class supply chain comes in. By creating digital infrastructure that connects engineers and supply chain teams with a vetted global network—across the U.S., China, India, and Mexico—we give companies access to the kind of sourcing, speed, and execution power that was previously only available to the biggest players. And we’ve made it easy to tap into: one platform, full visibility, rapid DFM feedback, and rapid lead times.

The mission: empower innovators to create by breaking through bottlenecks of traditional sourcing and manufacturing. But today, we’re doing that at a scale and level of sophistication that makes even the most complex programs feel achievable.

Fictiv describes itself as a “digital manufacturing ecosystem.” For those unfamiliar, what exactly does that mean—and how is it different from traditional contract manufacturing?

When I describe Fictiv as a “digital manufacturing ecosystem,” I mean we’ve built a technology-driven platform that connects customers with a highly vetted, global network of manufacturing partners—while technical experts guide programs and work directly with customers. Think of it as combining the speed and transparency of modern digital tools with the scale and quality of a Fortune 500-class supply chain, along with a team of experts that guide customers from start to scale.

Traditional contract manufacturing usually involves managing suppliers directly, often through emails, phone calls, and long lead times. It’s highly manual and siloed, making it difficult to scale quickly or get the real-time insights needed to make fast decisions.

A digital manufacturing ecosystem flips that model. With us, customers get instant quoting, automated DFM feedback, and visibility into every step of production. More importantly, we take accountability for quality, delivery, and cost-efficiency, while leveraging distributed global manufacturing centers across the U.S., China, India, and Mexico. The result is faster prototyping, smoother scaling to production, and a lot less risk and overhead compared to managing a traditional supply chain.

But a digital manufacturing ecosystem like Fictiv doesn’t function independently from our guided experts who work closely with customers from product development and design through prototyping and full production.

With the U.S. experiencing its largest surge in factory investment in decades, why do you believe talent—not machines or capital—is now the most pressing bottleneck?

The U.S. is seeing an unprecedented wave of factory investment—billions of dollars going into new plants, automation, and advanced technologies. But none of that means much without the right talent to run and optimize these systems. You can buy the most advanced machines in the world, but they’re only as good as the engineers, operators, and supply chain professionals who know how to use them effectively.

Over the past decade, we’ve seen a widening skills gap in manufacturing. Many of the most experienced professionals are retiring, and younger generations haven’t been entering the field at the same rate. On top of that, modern, digital manufacturing requires new skill sets—digital literacy, data analysis, and familiarity with AI and automation—which traditional training programs haven’t kept up with.

That’s why talent is one of the biggest bottlenecks right now. Capital can be deployed, and machines can be bought, but building and retaining a skilled workforce takes time, investment, and a culture that values curiosity and innovation. I believe solving this talent challenge—through training, upskilling, and better collaboration between tech and manufacturing—is critical to unlocking the full potential of this factory investment boom.

You’ve warned about a projected shortfall of 1.9 million skilled manufacturing jobs by 2033. What systemic issues are causing this gap, and what should the private sector be doing differently right now?

The projected shortfall of 1.9 million skilled manufacturing jobs by 2033 comes from the National Association of Manufacturers. I believe this gap is the result of deep, systemic issues that have been building for decades. For too long, manufacturing has been undervalued as a career path in the U.S., and we’ve failed to invest in developing the next generation of skilled workers. Meanwhile, the industry itself has evolved rapidly—shifting toward advanced technologies, digitalization, and automation—creating a demand for new skill sets that traditional education and training systems haven’t been designed to address.

Some reasons for this include:

• Aging Workforce: A large portion of the skilled workforce is nearing retirement, and there aren’t enough younger workers trained to fill those roles.
• Perception Problem: Manufacturing is still often viewed as outdated or less desirable compared to tech-driven industries, even though modern manufacturing is as innovative as software.
• Skills Gap: There’s a disconnect between the advanced technical skills employers need—data analysis, robotics, AI integration—and what is being taught in schools and vocational programs.

The private sector needs to take a more active role in fixing this. That means:

• Investing in Apprenticeships and Upskilling: Companies should create robust training programs that equip workers with both traditional and digital manufacturing skills.
• Partnering with Schools and Universities: Early outreach and education can help reshape perceptions of manufacturing and prepare students for high-tech, hands-on careers.
• Leveraging Technology: Digital platforms like Fictiv democratize access to manufacturing expertise, enabling teams to work faster and smarter without requiring decades of on-the-job experience.

You’ve advocated for hands-on STEM education and apprenticeships as a solution. Can you share examples of what this looks like in practice, especially at Fictiv or among your partners?

As an engineering student at Stanford, I benefited from hands-on education (as well as my time at Ford), so I’m deeply committed to STEM education and apprenticeships. In my opinion, they’re critical to bridging the skills gap because they allow people to learn by doing—not just in theory, but on real machines and real projects. I’ve seen how powerful this is both at Fictiv and among our partners.

At Fictiv, we’ve made a point of partnering with universities and STEM organizations to support hands-on learning. For example, we’ve worked with Formula SAE student teams to provide precision parts for an electric race car (which later competes nationally in an FSAE event), while also mentoring them on design-for-manufacturability and rapid prototyping. It’s an opportunity for students to see how their CAD models translate into real components, understand the trade-offs of different manufacturing processes, and get exposure to the same digital workflows that industry leaders use.

I believe the future of manufacturing depends on these kinds of initiatives. It’s about giving students and early-career professionals real-world exposure to modern, tech-driven manufacturing environments. This combination of hands-on experience, mentorship, and digital tools is what inspires the next generation of builders and prepares them to hit the ground running.

In what ways do you see Gen Z’s relationship with manufacturing fundamentally different from previous generations—and how is Fictiv addressing that cultural disconnect?

Gen Z’s relationship with manufacturing is fundamentally different because they’ve grown up in a fully digital, on-demand world where speed, transparency, and purpose are the norm. Traditional manufacturing—often seen as slow, opaque, and heavily manual—feels misaligned with their expectations for instant information and seamless digital experiences. There’s also a cultural disconnect: while older generations may view manufacturing as stable and hands-on work, Gen Z often associates it with outdated facilities rather than high-tech innovation.

Some generational differences include:

• Digital-first mindset: Gen Z expects real-time visibility and digital tools for everything they do—whether it’s tracking a package or building a product.
• Desire for purpose: This generation prioritizes sustainability, innovation, and impact. They want to know their work contributes to something meaningful, like advancing clean energy or robotics.
• Low tolerance for inefficiency: Manual processes, long lead times, and siloed communication systems feel foreign to them.

We’re reimagining manufacturing to look and feel more like the digital experiences Gen Z values. Our platform provides instant quotes, automated DFM feedback, and real-time production tracking, all in a cloud-based environment. We also lean into sustainability and impact messaging—highlighting how our work enables EVs, climate tech, and life-saving medical devices—to resonate with Gen Z’s values.

Culturally, we try to bridge the narrative: manufacturing isn’t just about machines; it’s about solving some of the world’s biggest challenges. By framing manufacturing as a tech-driven, mission-oriented career path, we make it more attractive to the next generation.

Automation often sparks fears of job loss. How is Fictiv’s technology actually helping elevate workers, rather than replace them?

Automation in manufacturing often gets a bad rap because it’s seen as a threat to jobs, but I see it differently. At Fictiv, our technology is designed to elevate workers, not replace them. Instead of automating people out of the equation, we’re automating the repetitive, low-value tasks—like quoting, scheduling, or tracking parts—so engineers, supply chain teams, and operators can focus on the work that truly requires their expertise: solving complex problems, designing better products, and driving innovation.

By giving workers real-time visibility, instant DFM feedback, and access to a global network of vetted manufacturers, we’re effectively acting as a force multiplier. It’s like handing teams a digital command center where they can make smarter, faster decisions with fewer bottlenecks. This not only improves productivity but also upskills the workforce—because people get to engage with higher-level decision-making, advanced digital tools, and data-driven problem solving rather than chasing paperwork or vendor calls.

Fictiv recently launched Materials.AI, a ChatGPT-powered assistant. How does it work in practice, and what kinds of decisions does it help engineers make more effectively?

Materials.AI is designed to act like the materials expert every engineering team wishes they had on call 24/7. In practice, it uses a combination of Fictiv’s 10+ years of manufacturing data, process knowledge, and AI capabilities—powered by ChatGPT—to guide engineers through critical decisions about materials and manufacturability.

Engineers can ask Materials.AI questions like, “What’s the best aluminum alloy for this part under high thermal stress?” or “Which plastic resin offers the best balance of impact resistance and cost for injection molding?”

Instead of relying on trial-and-error or waiting days for supplier feedback, the tool provides immediate suggestions based on both mechanical properties and real-world manufacturing outcomes.

More broadly, how are you using AI and machine learning across your platform—from quoting and DfM analysis to production oversight and quality control?

AI powers instant quoting by analyzing CAD files within seconds, factoring in part geometry, materials, and historical data to deliver accurate cost and lead-time estimates. It drives automated Design for Manufacturability (DfM) feedback, flagging potential issues like thin walls or complex features while suggesting improvements in real time.

Fictiv supports six different types of industrial 3D printing, with next-day delivery in some cases. How have you built the infrastructure to enable such speed and scale, and which industries are benefiting most?

We’ve built our 3D printing infrastructure with speed and scale in mind by combining a digitally orchestrated platform with a highly vetted global partner network. Every order goes through our cloud-based system, which uses AI to analyze CAD files, automatically select the best technology and materials, and route jobs to the right partner based on capacity, location, and quality performance. This orchestration—combined with regionalized production hubs in the U.S., China, Mexico, and India—enables next-day delivery for certain parts while maintaining strict quality standards.

The industries seeing the greatest benefit are those where rapid iteration and precision are critical, such as aerospace, EVs, medical devices, robotics, and consumer electronics. These sectors rely on our ability to provide functional prototypes and production parts quickly, so their engineers can test designs, reduce time-to-market, and respond to fast-moving customer demands.

As someone who has spent time both in software development and factory operations, how do you think the relationship between cloud software and physical manufacturing will evolve over the next five years?

I believe we’re on the cusp of a fundamental shift where cloud software becomes the central nervous system of manufacturing, bridging the gap between digital design and physical production in ways we’ve only started to see. Over the next five years, I expect three key trends to define this evolution:

Digital manufacturing platforms will connect every stage of production—from design to delivery—into a single, transparent data layer. Engineers and supply chain teams will have instant visibility into part status, quality metrics, and logistics, much like tracking a software build or code deployment.

Just as cloud computing transformed how companies deploy software, digital manufacturing will make it possible to “spin up” production capacity on demand. This will give companies unprecedented flexibility to scale operations globally without heavy capital investment.

Digital platforms will integrate advanced AI models that continuously learn from data across materials, machines, and processes. This will automate critical decisions—from material selection to cost optimization—empowering teams to iterate faster and with greater confidence.

Finally, as you look toward the next decade, what excites you most about the intersection of AI, robotics, and manufacturing—and where do you think the next big leap will come from?

One of the things that excites me most about the next decade is how AI and robotics are converging to make manufacturing more adaptive, intelligent, and scalable than ever before. We’re moving toward a future where factories can essentially “think for themselves”—using AI to analyze real-time data, predict problems before they occur, and continuously optimize production lines without human intervention. This won’t replace people, but rather elevate the role of human ingenuity—freeing engineers and operators to focus on innovation rather than firefighting.

In my view, the next big leap will come from fully autonomous, AI-driven production cells that can switch between product types with minimal reprogramming or downtime. Combine that with robotics and advanced additive manufacturing, and you’ll see hyper-personalized products and rapid, on-demand production at a global scale.

The convergence of AI and robotics will unlock on-demand, hyper-personalized manufacturing at global scale, reducing waste and accelerating innovation like never before.

Thank you for the great interview, readers who wish to learn more should visit Fictiv.