How A.I. is revolutionizing the concept of a high-value-add job
Charles D. Morgan
IS IT A “correction,” or is it A.I.? That’s been the gist of the speculation surrounding the recent massive layoffs from some of the biggest companies in the business world: UPS, some 34,000 employees; Verizon, 15,000 jobs, mostly through layoffs; Amazon, 14,000 employees; Target, nearly 2,000 employees. Amazon’s CEO, Andy Jassy, says his company’s layoffs have nothing to do with A.I., but, rather, with overexpansion. “If you grow as fast as we did for several years,” he said, “the size of businesses, the number of people, the number of locations, the types of businesses you’re in, you end up with a lot more people than what you had before, and you end up with a lot more layers.”
His comment about overexpansion is true enough, but I’ll tell you this. At my company, First Orion, we haven’t added a significant number of people in several years, and our revenues have doubled. Much of that is due to automation augmented by A.I. Which brings me to the subject at hand: What does a “high-value-add job” look like in today’s business world, and how much influence does A.I. have in that picture?
I am a serial entrepreneur, meaning I’ve spent most of my life seeking ways to provide high value to paying customers. My first job out of college was working for IBM as a “computer engineer,” a new concept back in the 1960s. But even within the corporate confines of IBM I acted as an entrepreneur, staking out my own territory in Northwest Arkansas, far from the Little Rock home office, so I could operate on my own time and in my own way. I was instrumental in selling Sam Walton his first computer, and it was probably that act that led me down the path I’ve been on ever since. In terms of “high-value-add,” just think of what computers have meant to the success of Walmart. And I, as someone who understood and could explain computers and data management, was in a position to provide high value not just to Sam Walton, but to many, many others.
In time, I left IBM and joined a small Conway-based “service bureau,” which rented space on our computers to other companies, enabling them to streamline their processes from supply chain to payroll. That little company eventually became Acxiom, the $1.5 billion, 7,000-employee, Little Rock-based world leader in data management and database services, with some 1500 separate pieces of information on more than half a billion people around the globe. And for the past 17 years—since the dawn of the smartphone era—I’ve headed up First Orion, which began as a provider of scam and spam protection and today has evolved into the top provider of call protections and branded business solutions for many millions of mobile phone customers across the United States.
It’s not hard to detect a progression in that brief autobiography—a cultural, social, and commercial evolution. That is the old, old story: As the culture evolves, so too does the concept of high-value-add jobs. “For most of the 20th century, high-value roles were defined by expertise, credentials, and control over scarce knowledge (think doctors, lawyers, engineers, bankers). Today, those foundations are still important, but they’re no longer the whole story. Now, tools can access and apply knowledge at scale.”
It’s only fitting that that’s a quote from ChatGPT, the most widely used A.I. tool in the world. In this year of 2025, ChatGPT logs approximately 800 million active weekly users and sees around 4.7 billion monthly site visits. Chat and its cohort of other-branded A.I. solutions are changing the way we do almost everything today.
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THIS IS A huge, sprawling, global subject, of course, one that entire books have been, and will be, written about. But I have neither the time nor the inclination to write a book on the subject, so let me demonstrate my point by taking you to my latest little corner of the world and showing you the changes there.
I now spend a good portion of my weeks in Heber Springs, on the Little Red River. We’ve launched an executive retreat business here on the property, with state-of-the-art meeting facilities and a newly opened grand lodge. We’ve also expanded into the woodworking/furniture-making business, and that’s the realm where A.I. has been a hands-on game changer.
Designing and producing furniture is both a massive and an intricate undertaking. It begins with the wood, which usually takes several months to dry; to get around that, I imported two giant wood kilns from China that can dry large tranches of lumber in 10 days to three weeks. In the factory next to those kilns are several other machines—a four-sided router/planer, which takes a still-rough plank of wood and renders it clean and square on all four sides; a straight-line ripsaw for straightening the bows out of any board; and the CNC machine, which we use to make all the individual pieces that go into constructing any item of furniture—a dining table, a chair, a bed frame, a chest of drawers. CNC stands for Computer Numerical Control, which refers to the automated control of manufacturing tools by a computer.
These and other machines we use may not in themselves be A.I.-run, but A.I. is infinitely useful in teaching our people both how to manage and operate the machines as well to solve the many problems we run into in designing and manufacturing a piece of furniture. For example, we have a very complicated five-axis machine that we use for turnings and routings of table legs and other intricate pieces. Occasionally we have issues—why is our finish not turning out the way we expect?—and A.I. helps us figure out what’s gone wrong and why.
Or take our rotary table, which we use to rotate a piece of furniture so the finish can be applied evenly without having a human doing the rotating (and leaving fingerprints all over the wood). The thorny initial problem was, What sort of transmission should we use for the rotary table, and what kind of motor should we use to drive it? We humans spent days racking our brains to come up with an answer, and then ChatGPT came to the rescue. “You need a worm-drive gearbox,” Chat said.
My point is that, like any other business, we use A.I. on both ends of the spectrum, from initial teaching to ongoing problem-solving. And in the process, we’ve turned a bunch of what I would call former furniture-manufacturing “amateurs” into “experts” at knowing how to coax much-needed information from the ultimate expert, A.I.
And remember, all of this is happening in rural Arkansas, which historically hasn’t been known for creating high-value-add jobs. But that’s precisely why I wanted to start this business here, and all the employees who’ve learned to run these very advanced machines are local residents who’ve now lifted themselves into a new category of expertise and demand. Because they now know how to guide and direct A.I. to do these complex tasks. They’re bona fide “A.I. Whisperers,” if you will.
Even I, a mechanical engineer trained to solve all sorts of problems, have come to rely on A.I. for projects that in the past I would’ve either slaved over for weeks or hired others with the proper expertise for the job. For example, we needed to design a factory for our woodworking. There are scores of complicated, interconnected decisions that need to be made in designing an efficient manufacturing facility, and I originally planned to turn the assignment over to an expert. Then one day I casually tossed out a few questions to ChatGPT, and I never considered looking anywhere else again.
Here’s the thing: A.I. used to be just a tool, a helpful assistant. Now the helpful assistant is taking, and owning, the boss’ job. My daughter is a college professor who teaches two advanced courses, and a few years ago she worked for literally weeks creating a syllabus for the first one. Then when she was asked to teach the second course, which is a highly related overlap class to the first course, she initially considered hiring a teaching assistant to prepare the syllabus for the new course. Instead, she hired ChatGPT, who knocked it out of the park—and did it a thousand times faster than any teaching assistant could’ve done.
At First Orion, A.I. saves us both a whole bunch of time and a ton of money. For example, when we get a new customer for branded communication, we have to be sure the person we’re signing up isn’t a scammer. “I’m ABC Electronics,” he says, “and I own this phone line.” Well, does he really? So we have to vet him to make sure (a) that ABC Electronics really exists and (b) that our new would-be customer doesn’t have a bad reputation. Before A.I., we did all that manually. We looked him up in databases, we consulted the Better Business Bureau, we checked with the phone company to make sure he owned that particular phone line. We even called up ABC Electronics and asked a few questions. At the end of which, we wrote up what we called a vetting summary. It was very labor intensive.
Today, bots can do most of that work, including calling the individual companies and asking questions. If the prospective customer hits certain thresholds, the bot may say, “Okay, A B C Electronics passed minimum standards, and I’ll go ahead and certify them as legitimate and we can begin branding their calls.” Or it may come up with a question mark of some kind. In any case, that data gets passed on to what I’ll call the supervisory level, meaning a human. But if that human has to check anything manually, it’s only one out of five applications instead of all of them.
We’re talking about a huge savings here. Branded Communications is the part of our business that we want to grow times 10, so at any one moment we might’ve had 200 people working on those vetting reports at, let’s say, $25 to $30 an hour. If each of those people could do only two of those inquiries an hour, we’d be paying $15 apiece to vet each potential new customer. With A.I., we can probably do it for a nickel each.
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IT IS THE same story happening over and over, no matter where you look and what kind of business you look at: the A.I. shift from job assistant to job owner, and from project to process. Meanwhile, here in rural Arkansas, technology has leveled the playing field. We didn’t used to have skilled workers, but now we can upskill our unskilled workers a whole lot faster than ever before.
“Value,” reports ChatGPT, “is moving from what you know to what you can uniquely do with knowledge in real-world complexity.” And in that new world, Silicon Valley’s got nothing on a really smart guy in Heber Springs, Arkansas, who can draw on the resources, and resourcefulness, of A.I.
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Charles D. Morgan is the chairman of First Orion. He and his wife, Susie, are the owners of James & James Furniture and Morgan’s at The Little Red.