Decoding The Myth: Will AI Replace or Reshape The Human Economy?

Last week, I sat down to write a rather somber piece on How Companies Can Execute AI Layoffs More Humanely? I was ready to dive into the inner workings of the corporate engines to illustrate how leaders can structure severance packages, enable displaced employees with upskilling programs, and lead with empathy.

One thing led to another and I found myself getting disillusioned with my original premise. The deeper I dug into the data, the more numbers started to not add. And what started as an inquiry into corporate empathy spiraled into a bizarre epiphany:

What if the narrative “AI is the reason behind mass layoffs” is actually a revival of the same old economic myth we’ve been falling for over and over again.

The advancements in technology replacing jobs is not a concept that has been newly introduced to us. It’s a 200-years old adage that dates back to the Luddites rebellion.

While this earliest instance of technological advancement displaced skilled artisans in the textile industry, the Industrial Revolution eventually generated an array of industries that did not previously exist.

The same macroeconomic fundamentals appear to be at play today.

Over 157,000 workers were impacted globally across more than 420 companies, largely driven by Artificial Intelligence (AI) restructuring. Parallelly, tech job postings, by May 2026, surged by 23% with paygrade also going up by 15%.

This brings me to my original conundrum: is AI truly the driving force behind the bloody theater of corporate layoffs? Or are we at an inflection point of a macroeconomic promise of job creation. 

To understand what’s actually happening today, we need to stop looking at the tech, and start looking at history. Because as it turns out, we have seen this exact movie before.

The ATM vs. The Bank Teller Debacle

Every time humanity invents a sharper tool, we collectively lose our minds imagining our own obsolescence.

Take the automated teller machine (ATM). When ATMs began proliferating, the consensus was absolute: the bank teller was history. It was a simple, logical equation, if a machine can dispense cash, you don’t need a human to do it.

Except, as essayist David Oks pointed out, that is not what happened at all.

By dramatically lowering the cost of operating a bank branch, ATMs made it financially viable for banks to open vastly more branches. And what do you need to staff those new branches? Humans. While the number of tellers per branch dropped, the sheer volume of branches skyrocketed. More importantly, the nature of the job shifted. Tellers stopped being glorified human cash-drawers and transitioned into relationship banking roles.

We saw the exact same thing happen in the 1980s with the invention of the digital spreadsheet (like VisiCalc and Excel). Before Excel, thousands of clerks spent days meticulously calculating numbers on paper ledgers. When the software arrived, it did the work of 100 clerks in three seconds.

Did accounting jobs vanish? No. Because the cost of doing a financial calculation dropped to near zero, companies started demanding millions of calculations. They wanted projections, scenarios, and data modeling. The job of the “bookkeeper” shrank, but the job of the “financial analyst” exploded.

Jevons Paradox & Its Effect On Demand

There’s a beautiful, simple economic principle that explains this: Jevons Paradox.

An economist named William Stanley Jevons looked at James Watt’s newly improved steam engine. Watt had figured out how to make the steam engine wildly more efficient, meaning it consumed significantly less coal to produce the same amount of power.

Naturally, everyone assumed this meant England’s total coal consumption would drop. Why wouldn’t it? The machines were doing the same work with less fuel.

But Jevons noticed the exact opposite happened. Because the steam engine became highly efficient, the cost of steam power plummeted. Suddenly, it was cheap enough to be used in everything, including – textile mills, locomotives, steamships, and manufacturing plants. Cheap power unlocked massive new industries, which caused England’s total coal consumption to absolutely skyrocket.

Now, let’s substitute “coal” for “cognitive tasks”.

Right now, AI is driving unprecedented efficiency into cognitive labor. It makes writing a basic line of code, drafting a legal document, or generating a marketing summary incredibly cheap and fast.

If you look at this through a narrow lens, you might think: “Great, companies will just do the exact same amount of work they do today, but with 80% fewer humans.”

But history tells us that’s not how human desire or economics works. When a resource becomes dirt cheap, we don’t use less of it; we embed it into everything.

• In Software: Because code is cheaper to write, we won’t build fewer apps; we will build hyper-customized software for every niche business problem on earth.
• In Marketing: We won’t launch one broad ad campaign; we will launch 10,000 hyper-personalized campaigns tailored to individual consumers.
• The Labor Multiplier: To manage this explosion of output, companies will face a massive demand for human oversight. We will need armies of people to prompt the models, audit the data for hallucinations, integrate the systems, and apply human judgment to a torrential wave of automated content. The efficiency of the task creates an infinite demand for the output, which ultimately drives a massive demand for labor.

Enter The “Engels’ Pause” In An AI Shaped World

But here is where the thought spiral gets dizzying. If history promises us that more jobs are coming, how do we explain the very real, very painful reality of the current labor market? Walk into any tech hub, and economic optimism feels like gaslighting.

Headlines detail a relentless “layoff tsunami” sweeping through corporate sectors.

History has an answer for this pain, too, and it’s called Engels’ Pause.

During the early Industrial Revolution, incredible new textile machines were invented. Wealth skyrocketed and productivity soared. But for a period of about 50 years, the wages of the actual workers stagnated, and the transition was brutal. The old jobs were destroyed faster than the new infrastructure could absorb the workers.

The macro-economy always rebalances, but humans live in the micro-economy.

As recent research on modern labor dynamics shows, the friction of this transition is heavy. Companies are aggressively gutting human teams under the assumption that an AI can immediately bridge the operational gap. The result? Remaining staff are burning out, product quality is dipping, and institutional knowledge is being erased.

Are companies firing workers because AI can genuinely do their jobs today? Or are executives using “AI transition” as a convenient, investor-friendly narrative to hide a much cruder reality: correcting for pandemic-era overhiring and cutting costs to boost short-term stock prices?

The Rainmaker’s Distortion

This brings us to the final loop of the spiral: If AI is not the grim reaper of employability then is “AI layoff” a marketing narrative crafted by the tech rainmakers?

Rand Fishkin in his latest op-ed pointed out that the narrative “AI is coming for all the jobs” is a masterclass in enterprise marketing. If you are a tech executive selling enterprise AI software, how do you convince a Fortune 500 board to sign a multi-million-dollar software license? You sell it as a revolutionary force that will allow them to drastically cut their single largest line-item expense: human payroll.

The terrifying irony is that we might be witnessing a self-fulfilling prophecy driven by pure hype rather than actual economic reality. Boards are demanding layoffs because they bought into the “rainmaker” marketing. 

The layoffs happen not because the technology is ready to replace humans, but because the executives need to justify the exorbitant cost of the software they just bought.

The Lingering Question

So, where does that leave us?

If we look at history, technological unemployment looks like a myth, a phantom that appears at the dawn of every industrial revolution, only to vanish when new, unimaginable industries sprout up in its wake. The bank teller survived the ATM; the clerk survived Excel; the writer will likely survive the LLM.

Yet, knowing that the macro-economy will rebalance itself in a few decades does absolutely nothing for the person who lost their job this morning because a CEO fell in love with a pitch deck.

We are left staring at a profound paradox. Are we on the cusp of an automated utopia where human ingenuity is supercharged by machines, just like the accountants of the 1980s? Or are we trapped inside a high-stakes, fear-driven marketing funnel designed to inflate tech valuations at the expense of human livelihood?

Perhaps the greatest threat to our employment isn’t the artificial intelligence of the machine at all, but our very real, very human susceptibility to a seductive sales pitch.