The Narrow Aperture
AI freed up six hours. The boss took them. But what if the real question isn’t about time at all?
Nick Lichtenberg did me an extraordinary kindness in Fortune this week. In a piece called “AI Just Gave You Six Extra Hours Back. Your Boss Already Took Them,” he quoted a plant manager from Ohio alongside Google directors, McKinsey partners, the chair of KPMG, and Baroness Dambisa Moyo of the House of Lords. I want to honor that generosity by doing what any good frontline worker does when someone hands them an opening — walk through it and get to work.
Nick assembled a magnificent chorus of voices all circling the same question: artificial intelligence is compressing tasks that once took days into minutes, so what happens to the hours that are left? A two-week audit at AES is now done in sixty minutes. Fifty percent of Google’s code is written by AI. A KPMG partner’s meeting prep dropped by seventy-five percent. The Dun & Bradstreet CTO, Mike Manos, put it with admirable candor: “I got the eight hours to two hours, but now I can get twenty hours of work.”
Every answer in the piece is about speed. I want to offer an answer about sight.
The Word That Caught Me
Manos used the phrase “widening aperture” to describe what AI makes possible — more problems to solve, more projects to chase, a bigger version of the job. It’s a photographer’s word. An aperture is the opening in a lens that determines how much light gets in, and therefore how much of the world the camera can see.
Manos means throughput. More light, more volume, more work crammed through the pipe.
But there is another way to read that word. What if the aperture that needs widening isn’t the workload? What if it’s the worker’s field of vision?
This is what I have spent thirty-six years studying, from General Motors to Royal Enfield to the corrugated pipe factory I run today in Wooster, Ohio. The single most consequential decision any company makes is not which technology to deploy. It is how much of the business it allows the frontline employee to see.
Three Openings
When I talk about widening the aperture for the frontline employee, I mean three specific expansions of sight. Not metaphors. Architecture.
First, see the whole business. Not just your station, your cell, your eight-foot stretch of the line — but the system. How the product reaches the customer. How the order triggers the production run. How quality at your hands becomes reputation in the market. In most American manufacturing plants, this view is systematically withheld. The worker is given a task, a rate, a shift. The aperture is kept narrow by design.
Second, see how money is made. Most plant workers have never seen a P&L. They have never been told what margin means, what their line contributes to revenue, what scrap actually costs in dollars the company will never recover. Open this aperture and suddenly the worker isn’t a pair of hands. They are an economic actor who understands the consequences of their own judgment.
Third, see your own reward. Not a generic bonus. Not profit-sharing that feels like weather — good years, bad years, who knows why. A fixed base that says we value your presence — and a variable component, above that base, that says we will pay you what you’re worth. Worth measured not in hours logged or widgets counted, but in Capability Capital: the deployed intelligence, judgment, and problem-solving that only a human being with a wide aperture can deliver. The variable line runs directly from “I saw this problem, I applied my intelligence, I solved it” to “here is what that was worth to the enterprise.” That is getting paid what you’re worth — and worth is measured in the capability you bring, not the time you spend.
When all three apertures are open — when the worker sees the business, understands the economics, and can trace their variable reward back to their own deployed Capability Capital — something happens that no amount of AI acceleration can produce on its own. You get a human being who is invested. Not managed. Not monitored. Invested.
That is where the ministry manifests.
The Suppression
So why don’t more companies do this? The standard excuse is that frontline employees aren’t capable of understanding the business. They lack the education. They lack the context. They wouldn’t know what to do with the information.
I have heard this excuse on four continents, in seven languages, across three decades. And I will tell you what it actually is.
It is fear.
Not fear that the worker can’t comprehend the business. Fear that the worker will comprehend the business. Because a worker who sees the whole system — who sees the margin, who sees what their labor actually generates, who sees the delta between what they produce and what they are paid — is a worker who can see the extraction. And visible extraction has to be justified. And justified extraction eventually has to be shared.
The narrow aperture is not a training failure. It is a design choice. The frontline is kept in the dark not because they can’t handle the light, but because capital cannot handle being seen.
Think about how perfectly this explains the pattern in Nick’s Fortune piece. Every executive he quotes is talking about what to do with the time AI freed up. Not one of them is talking about showing the worker where the value went. Manos says he can now get twenty hours of work out of what used to take eight. Growing for whom? The KPMG chair says “my business should be growing, and will grow.” He doesn’t say who shares in that growth. He doesn’t have to. The aperture is narrow enough that no one on the frontline can do the arithmetic.
The Harvard Business Review study Nick cites found that AI early adopters experience work as more intense — a phenomenon Boston Consulting Group researchers have taken to calling “AI brain fry.” Of course they do. They’re running faster on a treadmill they cannot see the end of, producing value they cannot trace, for a reward structure that hasn’t changed. The aperture of the task got wider. The aperture of understanding stayed shut.
The Proof That’s Been Hiding in Cleveland
For anyone who thinks what I’m describing is utopian, I have two words: Lincoln Electric.
Lincoln Electric is a welding equipment manufacturer headquartered in Cleveland, Ohio — sixty miles from my plant in Wooster. It has been in continuous operation since 1895. It has not laid off a single employee for economic reasons since at least 1948, and possibly since 1925. It has paid an annual profit-sharing bonus to every employee, without exception, every single year since 1934. That is ninety-one consecutive years of shared prosperity.
And it is ferociously, ruthlessly competitive. Lincoln Electric drove General Electric out of the welding industry. Its production employees are among the highest-paid industrial workers in Cleveland. Its revenue exceeds $3.8 billion. This is not a soft company coasting on goodwill. This is a company that wins — and wins because of how it treats its people, not despite it.
How? The aperture is wide open. All three openings, built into the architecture from the beginning.
Lincoln’s frontline workers see the business. An employee advisory board has met with the president every two weeks since the company’s early days. Open-door policy. Complete transparency on how piecework rates are set — and once set, those rates are guaranteed forever. The worker has the right to challenge every change.
Lincoln’s frontline workers see how money is made. They understand that when there is no profit, there is no bonus — and that when profit grows, the bonus pool has no upper limit. The company sets aside roughly a third of pre-tax profits for the annual bonus. In recent years, that pool has exceeded $100 million. The average bonus has run around $33,000 per employee — on top of wages that already lead the market.
Lincoln’s frontline workers see their own reward. The piecework rate is the fixed base — it says your presence and your labor have value. But the bonus is the variable, and it is calibrated to Capability Capital. Every employee is individually evaluated twice a year on four dimensions: output, quality, dependability, and — this is the one that matters — idea generation and cooperation. Not just how fast your hands move. How well your mind works. The worker who sees more, thinks more, and solves more gets paid more. They are getting paid what they’re worth — and worth is measured in deployed intelligence, not hours on the clock. The line from capability to reward is direct, legible, and real.
Since 1955, the average annual bonus has run at roughly seventy-seven percent of base pay. Read that again. Lincoln Electric workers routinely take home nearly double what they’d earn at any comparable manufacturer — and the company is more profitable for it, not less.
The Recession Test
But does it hold under pressure? In 1982, Lincoln Electric’s revenue dropped forty percent — from $450 million to $220 million — as every one of its traditional markets collapsed simultaneously. At any other company, that’s a layoff of a third of the workforce, minimum. Every CEO in Nick’s Fortune piece would have started cutting heads.
Lincoln didn’t lay off a single person.
They reassigned about fifteen percent of production workers to maintenance, to clerical work, to sales. Average pay was roughly halved. Executive compensation was cut too. Everyone absorbed the shock together. And the company stayed profitable. And it still paid the bonus.
When the recovery came, Lincoln didn’t have to rebuild institutional knowledge from scratch. It didn’t have to recruit and retrain. The intelligence was still there. Every worker who had been reassigned came back to the line with a wider view of the business than they’d had before — because they’d seen other parts of it during the downturn. The aperture had actually expanded through the crisis.
The well didn’t run dry. It deepened.
Amberg’s Twenty-Year Witness
Lincoln Electric is the American proof. Let me offer a European one.
Siemens operates a factory in Amberg, Germany, that kept the same 1,100 employees for twenty years while technology evolved around them. Those workers were not replaced by automation. They were formed alongside it. And over those two decades, they generated eight times the business output.
Same people. Same headcount. Eight times the result. Not because the machines got faster — though they did — but because the humans got wider. Their aperture expanded year by year. They understood the system. They understood the economics. They understood their role in an enterprise that was growing because of them, not in spite of them.
Siemens calls Amberg its “factory of the future.” I call it the factory that took the aperture seriously.
The Order of Operations
Here is where I part company with nearly every voice in Nick’s article.
The entire conversation — at Google, at McKinsey, at KPMG, at Dun & Bradstreet — starts with the tool. We deployed AI. We got these efficiency gains. Now what do we do with the humans?
That is the wrong sequence. Intelligence deployment precedes AI application. You widen the aperture first. You invest in the frontline worker’s ability to see the business, understand the economics, and connect their contribution to their reward. Then you hand them AI — not as a surveillance instrument or a speed multiplier, but as an amplifier of judgment they already possess.
A worker with a narrow aperture plus AI equals faster extraction until the well runs dry. The company milks the economic value of the knowledge that AI captured from past practice for maybe ten or fifteen years. But there is no new knowledge being developed, because humans develop knowledge. And then the well runs dry.
A worker with a wide aperture plus AI equals compounding intelligence. Because that worker knows what to ask the AI. They know what to question in the AI’s output. They know what the AI is missing — the tacit knowledge of the line, the customer, the slight change in the sound of the extruder that means the temperature is off. AI has no nose. It has no fingertips. It has no thirty years of pattern recognition earned in the smell of resin and the feel of a pipe wall. But it has tremendous analytical power — and in the hands of a worker who can see the whole business, that power compounds rather than extracts.
Lincoln Electric understood this before the word “artificial intelligence” existed. James F. Lincoln’s foundational insight, laid out in his 1951 book Incentive Management, was that workers suppress their own productivity when they fear it will cost them their jobs. The narrow aperture isn’t just intellectually confining. It is economically rational for the worker. If you can’t see where the value goes, and you suspect it isn’t coming back to you, why would you give your best thinking to the enterprise? You’d be funding your own replacement.
Lincoln’s answer was the Guaranteed Continuous Employment Plan. Your job is secure. Now give me your real intelligence. And the workers did. And the company became the most dominant force in its global industry for the better part of a century.
What Keynes Couldn’t See from Cambridge
Baroness Dambisa Moyo raised a haunting reference in Nick’s piece. John Maynard Keynes predicted in the 1930s that by 2030, technology would make a fifteen-hour workweek possible. Then he asked, with obvious anxiety, what people would do with all that free time. “Will they be contemplating God?” Moyo noted, adding her own worry about rootless young men around the world who are “not contemplating God in the manner in which we would want them to.”
I understand the anxiety. But I think Keynes — and Moyo — are asking the wrong question, because they’re imagining the freed hours as empty hours. Leisure. Void. Time without purpose.
The Ministry of Manufacturing offers a different answer. The freed hours are not free time. They are formation time. Time to learn the business. Time to understand the economics. Time to develop the judgment that makes a frontline worker not just fast but wise. Sanctuary — the safety to learn without fear. Ascension — the structured pathway to greater capability. Crucible — the real challenges that turn knowledge into mastery.
The workers at Siemens Amberg are not contemplating God in their liberated hours. They are doing something Keynes never imagined from the remove of Cambridge — they are growing into the technology rather than being replaced by it. And the workers at Lincoln Electric have been doing it since 1934, in Cleveland, in manufacturing, in the very heart of the Rust Belt that everyone else has written off.
Watch What Happens
So here is my answer to the question Nick’s article poses. AI freed up six hours. The boss took them. What now?
Open the aperture. Honestly. All three openings. Let the frontline employee see the business — the whole business, not the sanitized version. Let them see how money is made — the real numbers, the real margins, the real cost of the problems they solve every day. Let them see their reward — variable, specific, tied directly to their contribution, above and beyond base compensation.
Then hand them AI. Not as a replacement. Not as a treadmill set to a higher speed. As an instrument worthy of the musician.
And then watch what happens.
Watch the discretionary effort that no monitoring system can compel. Watch the problem-solving that no algorithm can replicate. Watch the compounding intelligence of a workforce that is invested — not because they were given a motivational speech, but because they can see the return on their own deployed capability.
Lincoln Electric has been watching it happen for ninety-one years. Siemens Amberg watched it happen over twenty. The companies that understand how to unlock this intelligence, engage their people, deploy the tacit knowledge they already have, and then layer AI on top? They are going to win extraordinarily.
The companies that simply cut — that keep the aperture narrow, harvest the AI efficiency gains, and send the savings to the balance sheet — will milk the well for ten or fifteen years. And then it will run dry. Because the humans who develop new knowledge will be gone. And AI, for all its magnificent speed, cannot develop what it has never seen.
The question isn’t whether AI gives you back six hours. It’s whether you have the courage to let your people see what those six hours are worth.
Venki Padmanabhan is a plant manager, former CEO, and the author of the forthcoming book Already Paid For: Why Unlocking Frontline Intelligence Beats Automating Workers Away. He writes The Long Game on Substack and is co-founder of the Capability Capital Institute.