The US Census counted nearly 240,000 manufacturing firms in America.
Only ~4,000 of them have fewer than 500 employees, of which only 8.8% of those are using AI in production.
A plant manager I spoke to recently runs a 180-person precision parts shop in Ohio.
He attended a regional AI in manufacturing workshop last fall and came back with a stack of vendor brochures and no idea what to do on Monday morning.
Before we get into what is changing that, quick question:
How is your plant currently accessing AI training and implementation support?
👋🏻 I'm Leonardo Ubbiali. This week we're looking at why a 200-person shop in Michigan is outpacing manufacturers ten times its size on AI, and what they found that most vendor workshops will never tell you.
79% of manufacturers who adopted AI saw unplanned downtime stay the same or increase. The technology worked but implementation didn't.
The Ohio plant manager knew that walking into the workshop.
He was not looking for a Volkswagen case study, and just wanted to know what to do on Monday morning with the team he had.
The AI conversation in manufacturing runs almost entirely on enterprise examples.
The case studies filling every conference panel share one thing: they require infrastructure, budget, and internal expertise that 98% of US manufacturers do not have.
Every vendor in the workshop room gave him the same answer. Get your data ready, train your team, then deploy our platform.
The problem is no vendor in that room had built anything for a manufacturer his size. And 47% of small manufacturers cite data quality as their top barrier.
That is solvable though.
What is harder to solve is sitting across from a vendor who claims their platform works for manufacturers your size and having no credible way to verify it.
It pairs Apple engineers and Michigan State faculty with small manufacturers through free in-person training.
The only output is practical techniques applied directly to the floor.
Block Imaging services and refurbishes CT scanners and MRI machines for healthcare providers across the US.
They are 200 people in Michigan. On April 30 and May 1, 2026, they hosted 260 manufacturers from 16 states at their facility for the inaugural Apple Manufacturing Academy Spring Forum.
The manufacturers inside that number did not get there by buying enterprise platforms.
They found one specific problem, tested one specific tool, verified it worked, and moved to the next one.
Block Imaging keeps coming back to the Academy.
That is the thing the Ohio plant manager could not find in that workshop room. A credible starting point from people who are not selling anything.
Four sessions run through July 2026. The next is on May 12 and 13, focused on data.
Five things you can do this quarter
The Prompt (copy this):
I'm a [YOUR ROLE] at a [PRODUCT TYPE] manufacturing company with [NUMBER] employees. We want to start using AI on the floor but don't have a dedicated data team or a large technology budget.
Our highest-friction manual processes right now: [LIST TWO OR THREE] Current systems: [ERP / MES / SPREADSHEETS] Biggest constraint: [TIME / BUDGET / SKILLS / DATA QUALITY]
Tell me:
Which of our manual processes is the best starting point for a narrow AI pilot given our constraints?
What data do we need in place before deploying anything?
What should we look for in a vendor that works with manufacturers our size?
What does a realistic 90-day implementation look like without a dedicated data team?
What you'll get back:
A prioritized starting point for your first AI pilot, the minimum data requirements to run it, a vendor evaluation checklist sized for SMB manufacturers, and a 90-day plan that fits a lean team.
MaintainX 2026 State of Industrial Maintenance Report
58% of factory teams now use AI and 75% report measurable ROI in under six months. Yet 79% saw unplanned downtime stay the same or increase. Required reading before deploying anything on your floor.
Time to value: 15 minutes
Hit reply: The Ohio plant manager left that workshop without an answer. Does your plant have one?
I read every email.
Leo