We won’t fill manufacturing jobs and skills gaps by pushing more kids into coding bootcamps; we’ll fill them when we rebuild the industrial tech stack to reflect reality
Chicago, Illinois – June 24: Workers assemble Ford vehicles at the Chicago Assembly Plant. (Photo by Scott Olson/Getty Images)
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Over the weekend, I stumbled onto another article about how American factories can’t fill 400,000 open jobs. It’s full of stats, quotes, and the usual suspects: baby boomer retirements, immigration crackdowns, the college-or-bust myth, underfunded training programs. All true, all predictable, and all missing the point.
It’s not as simple as, “we need more workers in manufacturing.” Actually, we need to unlock more of the potential in the ones we already have.
The people running our factories aren’t just operators; they’re engineers, systems thinkers, and problem-solvers. But for too long, we’ve given them siloed, rigid, one-size-fits-all manufacturing execution systems (MES) that create technical barriers that don’t need to exist.
If we rebuild the industrial tech stack to reflect the real nature of frontline work, we’ll give the people already doing the work the power to improve it.
12.7 Million U.S. Manufacturing Workers, and No One to Work?
Currently, there are two camps: one warns that agentic AI-powered humanoid robots are going to replace factory workers, and the other argues manufacturing companies simply can’t hire fast enough. But the facts don’t fully support either position. The truth is:
- Automation, robotics, and AI aren’t coming in to change everything overnight. Our industry pretends to move fast, but in reality it moves pretty slow. And, with the high stakes of production line disruption, we need humans-in-the-loop (HITL), not lights-out factories.
- Modern manufacturers don’t necessarily need more “blue-collar” workers; they need a new architecture and a new tech stack.
Think of it like giving factory teams the same kind of modular, flexible systems that app developers or office workers already enjoy. In this way, the technology supports the real, messy, collaborative, digital-physical work happening on the shop floor: the work that requires critical thinking, hands-on expertise, and the ability to learn and adapt fast. You know — actual knowledge.
This brings me to a term that I think needs to die: “knowledge work.” This is the idea that only people sitting at desks, working with spreadsheets and Slack channels, are doing any “thinking.” This is not just outdated, it’s arrogant. The people debugging robotic systems, tuning process parameters, or troubleshooting a machine under pressure? That’s not “blue-collar” – that’s skilled cognitive labor. I think it’s time we stop worshiping the keyboard and start respecting the controller, the multimeter, and the SOP binder.
What This Looks Like in Practice
We won’t fill manufacturing jobs and skills gaps by pushing more kids into coding bootcamps, or outsourcing these jobs to robots. We’ll fill them when we rebuild the industrial tech stack to reflect the reality of work on the factory floor. This looks like:
- No-code, easy-to-use interfaces: We love IT, engineers, and system integrators. They provide insights, service, and are a key source of knowledge for the industry. But there simply aren’t enough system integrators, and they can’t be onsite all the time to run day-to-day operations or manage change.
The practical solution is to think past the existing systems and processes and give ownership and power to the people actually doing the work. This is a cultural shift toward citizen development in manufacturing, where frontline teams continuously innovate and optimize their processes. When frontline factory workers are able to test and iterate on tools or workflows themselves (without waiting on central IT), feedback loops tighten and improvement cycles shorten. By empowering our frontline workers to make real-time decisions, we not only build their capability and buy-in, but also promote resilient operations and processes that give us the flexibility to solve tomorrow’s problems.
- AI for operations: AI in manufacturing doesn’t need to be magic, it just needs to be designed for the people who do the work and built on infrastructure that’s flexible enough to evolve with the latest models. We need to think about AI as another tool or step function in productivity that we can incorporate to help solve real problems for real people on the shop floor. For instance, what if frontline workers could use AI to instantly convert existing SOPs into interactive, multilingual apps – without needing to learn how to code?
- Purpose-built production systems: If every factory and production line is different, and every operator brings unique knowledge, then their MES needs to be composable (made up of configurable, modular building blocks). A composable MES helps frontline teams tackle their most urgent day-to-day needs, while also setting them up to scale production and reconfigure their lines quickly, safely, and without a six-month implementation cycle. That’s how businesses stay competitive in a world shaped by supply chain shocks, shifting demand, and constant change.
The New (or No) Collar Economy
Beyond technology, we need to start treating frontline expertise as the backbone of modern economics, not a nostalgic throwback. We’re not going to get more people into factories until we stop treating those factories like second-class workplaces. And we’re not going to solve the skills gap until we stop pretending only certain jobs deserve the label “smart.”
As we build the tools that make the real work visible, let’s call it what it is: the new collar economy (or just drop collars altogether).