In this multi-part series on ASSEMBLY Audible, Bill Good, Vice President of Manufacturing and Supply Chain at GE Appliances, shares how the company is modernizing its plants, upskilling its workforce and integrating automation and AI to drive productivity and resilience. From redefining the employee value proposition after the pandemic to deploying AI tools that help operators diagnose equipment in real time, this conversation explores what it takes to scale advanced manufacturing in the United States — and why speed, talent and technology must evolve together.

This week, we’re focusing on the major impact AI is having on US manufacturing. We have a lot of questions to get through on that topic.

But first, I’d like to understand a bit about what you’re seeing as far as automation goes… how it is changing the types of jobs and skills manufacturers need. What skills gaps concern you most, and where do manufacturers need to rethink how they recruit, train and retain talent?

 
BILL:
It’s a question we’ve been working on for quite some time. If you go back to the pandemic, what we found was a shortage — people took themselves out of the workforce. There was a lot of fear about working in public and being around others. We didn’t let that crisis go to waste. We looked deeply at our pipeline and what we expected from people in manufacturing.

For decades, recruiting followed the same formula: this is the work and this is the pay. We flipped that upside down and focused on adapting the work to people, rather than adapting people to the work. That shift in mindset was significant.

Automation has also changed the game. Historically, operators performed very physical, difficult work. Today, much of that has been automated. We focus on automating dull, difficult and dirty work — the jobs people don’t want anyway — and moving associates into roles where they can add more value. That’s one piece.

The other is this… Think about a watch. An old analog watch simply told time. A smartwatch delivers health data, takes calls and runs apps — all from your wrist. The same exponential shift has happened in manufacturing. Equipment that once required turning a dial or flipping a switch is now run by computers. And you have to have skills to interface with the PLC and make adjustments.

For example, in thermoforming, we bring an extruded flat sheet of plastic into a process where it’s heated — similar to a toaster oven — until it melts and is molded to create the inside of a refrigerator. An operator must interface with a PLC to adjust heater temperatures and ensure uniform plastic thickness without weak spots. That’s just one example of the complexity in today’s equipment.

As a result, jobs have been upskilled. We are far less reliant on physical lifting and molding roles and much more focused on technical capability. And we reserve the jobs for operators that they may install parts on finished goods.

When we talk about gaps, there are three major categories. First is maintenance — associates trained to work on complex equipment. Decades ago, many people grew up on farms or worked on cars and developed hands-on technical skills. Today, fewer people work on their own vehicles. That skill set is in high demand and difficult to find.

Second is tooling — tool builders who work on stamping presses, molding tools and related systems. That capability is also scarce. So we have to develop those skills.

Third is equipment operators, whose roles now require a different technical skill set than in the past.

To address these gaps, we’ve developed internal programs — FAME programs, maintenance apprenticeships — building talent from the ground up, including tooling expertise and advanced operator capability.

 
ASSEMBLY:
We’ll be talking a lot more about automation’s impact next week, as well as your digitization efforts and use of digital twins. But let’s shift today’s talk to AI. As you modernize operations and bring more complex processes in-house, where do you see AI creating the biggest advantage inside your plants?

 
BILL:
There are areas where you can create a closed-loop system. With AI, one of the biggest opportunities is equipment performance. AI allows you to reduce dependence on one individual’s experience or depth of knowledge.

You can create systems where equipment diagnoses itself, makes adjustments and optimizes performance. An operator still oversees the process and intervenes when necessary, but AI becomes a force multiplier.

In our industry, AI will be a game changer. It will be as transformational as the internet or the PC. That’s why we are doubling down on it. Its impact on manufacturing will be that significant.

 
ASSEMBLY:
With AI becoming more embedded in equipment and diagnostics, how do you think about the balance between automation and human expertise on the factory floor?

BILL:
There will always be a handshake between humans and technology. We need human interaction and interface.

However, AI can provide a meaningful advantage. Companies that democratize the use of AI and build organizational capability around it will lead. That’s what we are focused on — embedding AI in ways that enhance human capability, not replace it.

 
ASSEMBLY:
Manufacturing has an awareness and perception challenge, especially with younger workers. As you expand U.S. operations, how are you working to change that narrative and attract the next generation of talent? Does AI play any role in attracting new talent?

 
BILL:
After World War II, manufacturing jobs represented 25–30% of total U.S. employment. Today, that number is closer to 9–10%.

Young people interact daily with strong consumer brands — Amazon, Starbucks, Walmart — but manufacturing has lost visibility. It has become almost an afterthought.

We need to move upstream and build awareness starting in middle and high schools. Manufacturing jobs consistently pay 30–40% more than many other blue-collar roles, and the benefits multiplier is strong.

We also have to change the perception of what these jobs look like. They are not the hot, dirty environments of 50 years ago. We’ve invested in HVAC systems, air turnover and improved working conditions. We’ve built cafés instead of traditional cafeterias to improve the associate experience.

We’ve placed employees at the center of the environment. The people who take the leap into these jobs are paid fairly well, earn a living wage and enjoy the work. We simply need to tell the story better and rejuvenate interest, especially for those who may not want to pursue a college degree. Manufacturing is a strong pathway to a good living.

 
ASSEMBLY:
You’ve talked about speed being critical in manufacturing. Can you share a practical example of how you’re using AI or digital tools to help operators diagnose problems faster and protect uptime?

BILL:
I’m fearless when it comes to tackling something because I’m comfortable breaking problems apart and putting them back together. YouTube has changed the game — if you want to learn how to do something, there’s a video for it.

We are applying that concept using AI. Operators can interface with equipment and essentially pull up step-by-step guidance or video-based diagnostics. The system evolves over time, improving based on prior incidents and solutions.

If a piece of equipment fails in a way that only happens once a year, it’s challenging to expect an operator to remember exactly how to fix it. An AI assistant — whether a bot or an agent — can guide them step by step, reference what happened previously and accelerate resolution.

Speed matters in manufacturing. The ability to identify, respond to and solve a problem quickly can determine whether it’s a profitable day. AI processes information faster than the human brain when it comes to diagnosing patterns and suggesting solutions (problem solving).

You still need someone to execute the task, but arming operators with the right information in real time is a game changer. In one of our plants, 1% of lost output equals $1.5 million annually. The multiplier effect is enormous.

 
ASSEMBLY:
When you’re investing billions into facilities and new capabilities, how do you pilot new technologies — like AI — and scale them across multiple plants effectively? What is your advice for other manufacturers?

 
BILL:
I’ve been a student of the Toyota Production System for most of my career. Toyota built a manufacturing system that many have attempted to duplicate and that has been wildly successful in the U.S. That philosophy has influenced how I think.

We build a model cell, then a model line, then a model value stream and eventually a model plant. We pilot new technology or capability in one plant first.

Each year, I manage a capital budget to modernize plants — whether through automation or new product introductions. I use discretionary capital to make bets on ideas. Once we perfect an idea, prove it out and demonstrate a return on investment, we scale it across our plants.

 
ASSEMBLY:
Thank you so much, Bill, for joining us today on ASSEMBLY Audible. I am very excited to continue this conversation with you next week, where we’ll focus on automation and digitization. We’ll also see you at the Manufacturing and Automation Exchange taking place March 24-26 in Nashville, Tennessee. And you, our listeners, are all invited to attend, and hear Bill in our panel discussion on reshoring Wednesday afternoon. Thank you for listening today. I hope you’ll join us again soon.