Good Morning,

Recently I’m trying to speculate, ponder, analyze and think not just about what AI will do to the future of work or the workforce but capitalism, rule of law, economics and the labor market as a whole in terms of the socio-economic caste systems it is contributing to in the United States. I find myself impacted by the gulf between the haves and have-nots. The demand for compute of AI is actually stressing the entire system. I am concerned the pretext of (which I will hereby refer to as ) the demand for compute is eroding democracy itself. Everytime the numbers come out (like the job numbers), I see the spectre of AI impacting them. Later in this article I discuss some of the reasons the AI bubble is building negative momentum.

When I think about the tightening labor market in the U.S., my base case is that AI will accelerate the erosion of equality, increase the churn of peak aged men in the labor force and erode the share of GDP that goes to workers. These are of course already trends with considerable and significant momentum in the U.S. history of capitalism and democracy. The economics of the elite is the new normal, where many of us have noticed that American Venture Capitalists are like royalty in the Trump Administration and even present as the chosen authority in the “task forces” of the Kevin Warsh led of the Fed. What does that tell you about the future? When you look at the economic picture and macro trends, a few things begin to become clear.

Long-term unemployment fell in July, according to the July 2026 jobs report - not because they found work, but because they stopped looking. Most of the new jobs are in healthcare, so American men are having a harder time of it inspite of being more likely to be so-called AI-natives (workers who default to AI to solve problems).
U.S. workers saw their share of the U.S. economy (GDP) slide to a record low in the second quarter, according to the Bureau of Labor Statistics (BLS).
When 23% of the US workforce is 55 or older: the retirement wave is coming but AI isn’t likely to make up for this churn of talent from the labor market, especially when immigration has been slowed by The Trump Administration to a trickle.

Obviously the unemployment rate is now an outdated metric to track the important things that are happening here. Yet this is all of these years later the key metric the President, the political media, The Federal Reserve and economists tend to use. With the gig economy and with aging populations and some of us taking care of our parents, it’s complicated. The future of work is no longer binary.

U.S. Labor Participation Rate is Trending Down

The U.S. labor force participation rate decreased to 61.4% in July. That’s far lower than most countries. AI is reshaping hiring and skill needs by more in areas of efficiency, flatter management systems at companies and reducing costs to be able to afford AI adoption, whose systems aren’t demonstrating or showing actual higher productivity or significant ROI.

I anticipate Generative AI will push labor participation down as a whole new generation needs to discover for themselves what the future of work might mean with less entry level opportunities in the traditional sense in this low-hire environment. AI is both a disruptor and a catalyst here. When people leave the job market and are no longer looking for work, they simply aren’t counted. On Friday we learned that Nonfarm payrolls fell 23,000 in July, confounding economists’ expectations for an 80,000 increase - that’s quite the shortfall.

Payroll revisions tell us a bleaker story than we were being told: In 2026, 1.4 million American workers have left the labor force.

Excluding the pandemic years 2020 and 2021, the labour force (participation rate) is at its lowest since 1976.

Generative AI doesn’t appear to be bringing more opportunities for American workers since 2022, in fact the K-shaped low-hire-low-fire economy with higher inflation is pretty toxic for quality of life and basic life affordability. Not just less opportunities, but more difficult choices in real American families and single households.

But the declining labor participation rate has mostly to do with an aging workforce, less immigration and a tighter labor market, some of which might be caused by contributing factors related to AI as well. The mental health impacts of technology and isolation many American men are feeling and experiencing aren’t present in any of these numbers.

But U.S. workers aren’t seeing the benefits of the GDP boost the datacenter roll-out is bringing the U.S. In fact, U.S. workers again saw their slice of the U.S. economy slide to a record low in the second quarter amid an ongoing productivity boom that is producing output gains which are outpacing wage growth, the Bureau of Labor ⁠Statistics reported on Thursday August 6th, 2026. If we tally the meta trend scores, it’s worrying to me:

Labor participation rate is down.
Workers share of GDP is decreasing
Exodus of worker from labor market is increasing
The percent of prime age men who are not working is increasing decade over decade (after each crisis)
The youngest and oldest workers are getting penalized in an AI-first job market the most
Workers aged 55+ make up 23.2% of the U.S. workforce and many are taking and will take early retirement
The debt being taken out in the AI Infrastructure push might worsen America’s debt-to-GDP ratio, national debt and the ability to make good decisions for the nation in the coming years
The cost of compute, and rising demand for AI compute will be peaking just as U.S. National debt payments begin to dangerly compound sometime in the next decade or next 15 years
Margin debt is rising so fast (in mid to late 2026) it is a leading indicator of a market bubble event

U.S. Debt to GDP Ratio might be Accelerated by AI’s Demand for Compute

The U.S. federal debt-to-GDP ratio is approximately 123% based on recent federal and economic reports showing a national public debt of roughly $37–$39 trillion compared to an annual gross domestic product of around $30–$31 trillion. This is expected to get worse in the coming years likely accelerated by the costs of building AI compute, fabs, datacenters and the circular funding of the project.

U.S. debt to GDP is increasing rapidly:

The Demand for Compute will lead to Sticky Inflation

It’s commonly understood that AI will significantly increase inflation or at the very least make higher inflationary more sticky (at least at this stage in the cycle). The annual U.S. inflation rate is currently about 3.5% for the 12-month period ending in June 2026, down from 4.2% in May.

Public debt-to-GDP ratios remain elevated in many advanced and emerging economies, as well as inflation that could be more systemic due to the pressure of the demand for compute. Even as the demand for compute is stoking geopolitical competition that’s creating dangerous bottlenecks that’s in a circular fashion pressuring inflation and the cost of said compute.

Read the Report

Trump’s bizarre Tariffs, the impulsive Iran war combined with his belligerently business friendly pro AI policies, are all incredibly inflationary. Consumer sentiment among American workers towards AI has been decreasing rapidly especially in the 2024 to 2027 period. Not surprising Trump’s polls regarding the war or the his performance on the U.S. economy appear to be correlated.

The very same younger men who tend to use Generative AI more frequently and who are more likely to be power users are the very same workers who seem to be most hurt by the economic consequences of AI generally speaking. You could even make the argument that the demand for compute of AI is hurting younger men at their peak working prime. The tighter labor market has a Gremlin looming, this is also the spectre of AI. While higher persistent inflation and lower wage gains (that aren’t keeping up) means they are becoming poorer during the AI boom. The potential of AI agents to increase layoffs is a persistent fear in several industries.

Obviously, when wage growth outpaces inflation, workers gain purchasing power. When inflation rises faster, real wages drop and everyday items become less affordable. So what happens when this occurs to an entire generation of men? Stuck in an affordability crisis as a tighter labor market favors women who tend to be more involved in the healthcare system, in service jobs that are more resilient and taking care of a fastly aging population?

During this AI boom in the mid 2020s in America, the top 10 percent of America’s financial elite are contributing nearly 50% of the consumer spending, according to Moody Analytics in January, 2026. Those top earners, defined as Americans making at least $251,000 in 2024 according to Census data, drove 49.2% of consumer spending in the second quarter of 2025. Is AI making us a less equal and meritocratic society? What sort of a world is the demand of compute going to lead to? Will whatever Generative AI becomes - empower society and give us more options? Or begin to take away our choices, freedoms and dignity?

Not only doesn’t Generative AI seem to be boosting productivity in a marked way, over the last three years when it’s become a bigger story of adoption, over the 3-year window leading up to (2023 to 2026) mid-2026, the positive wage growth trend (relative to inflation) you’d hope to see has recently stalled. Generative AI appears to be making many Americans poorer. Especially if they don’t have discretionary savings they can use in the boosted and artificially inflated equity market. This is creating a mounting socio-economic class divides around AI.

If Generative AI and the demand for compute are contributing factors to the widening the K-shaped economy, the affordability crisis in the 2020s should get worse in the 2030s. Furthermore AI’s contribution to GDP via datacenter construction isn’t reaching the wallets of consumers or most workers. It isn’t trickling down because AI adoption remains segmented. Therefore the demand for compute that is being afforded by circular and vendor financing is creating a whole new class of owners, while hurting the working class of the labor market. It’s literally eroding quality of life, affordability and opportunity for many to most Americans. It’s no great wonder they don’t love it.

Just in July, 2026 some 264,000 people left the labour force, meaning they are no longer working or looking for work. Who knows what their situation even is, but it’s probably not good and certainly unlikely to be better due to AI. Perhaps they are older workers who have taken early retirement due to AI’s arrival. Perhaps they are recent graduates waiting for better times. Some occupations have 30% to 50% of workers nearing retirement age and society has neither the labor from immigration, robots or AI agents that will be doing their job going forward. Those things don’t actually exist.

The higher debt levels exasperated by the demand for compute will actually complicate the U.S. dealing with its national debt in a responsible manner. The Federal Reserve supposedly have a 2% target for inflation, but the demand for compute will mean it will be nearly impossible to reach that level anytime soon. The Fed’s independence in an era of AI might be compromised. Generative AI could actually cause the consumer price index (CPI) to become elevated relative to historical norms, just like Apple and others raised prices due to higher HBM costs due to AI’s higher demand for compute and cost of compute (due to all the bottlenecks).

If AI contributes to a higher CPI for a prolonged period, consumers will be hurt by it.

U.S. consumers are becoming addicted to the equity (stock) market during the AI bubble. During the AI boom there are also suddenly “prediction markets” that are being pushed into our lives (as if gambling is a north star of our newfound collective mirror). Some retail investors not in labor market are the very men that are going to be the most hurt when the AI bubble pops. In general, as you know, the vast majority of stock market value is owned by the wealthiest households. Where bottom- and middle-income workers hold minimal equity, meaning surges in corporate profits like we are seeing with the AI boom or capital gains bypass them. The dangerous rise of wealth inequality magnified by the demand for compute, structurally creates and is going to create far more divisions, conflicts and risks in the American system and to our collective future that it now appears in 2026.

The BLS said that workers share of GDP is the lowest since the series began in 1947. The demand for compute is siphoning and imposing a wealth distribution to a minority of owners of Capitalism. This centralization of AI power thus means more workers need to become business owner if they wish to de-risk themselves in the years ahead. The trend essentially means that the benefits of AI’s productivity gains are accruing more toward business owners and shareholders ⁠than to workers through wage gains. This is going to be profounding disruptive to the American way of life and millions of Americans. Capital is being sucked up from the people to the enormous and accelerating demand for compute, including tax dollars, workers share of GDP and all other metrics.

The recent U.S. Payrolls told us the economy added 103,000 fewer jobs in May and June than previously estimated (these revisions are getting more common). Volatility in job creation and the decline of professional opportunities is not the thing that worries me the most though, it’s how AI’s demand for compute will impact people, consumers, workers and the majority of citizens in the years and decades to come in the big picture. Will all of that compute build an AI that benefits people? I’m not seeing much evidence so far that it will. What am I missing?

Addendum

Finally, how do we know we’re in an AI bubble? What are the signs and symptoms that you can think of?

Here are some of mine:

The massive capital expenditures (capex) on AI infrastructure (datacenters) are far outpacing actual monetization and diffusion to different companies and different sectors of said monetization.
There is this well-known metric called the cyclically adjusted price-to-earnings ratio. (CAPE / Shiller PE). So historically for the S&P the mean is about 17.40. Guess what it is today? It’s in the area of 42.39. As you may know, the Shiller PE—is a valuation metric created by Nobel laureate Robert Shiller to measure whether a stock market index (most commonly the S&P 500) is expensive or cheap relative to its long-term historical earnings power. We have data since 1928, and we are approaching the 2nd highest ever and might overtaken that 1999 level. While Earnings are great it’s being impacted by radical circular financing. Which for me means some of that demand isn’t real, it’s being artificially inflated.
Venture Capital is over-investing in very speculative AI startups related to AGI, RSI, AI in science, and “Superintelligence” themed AI labs, that are essentially low probability success moonshots. The glut of VC funding going into AI compared to other deserving industries is out of proportion and not sustainable.
The demand for compute is creating volatile pricing spikes in cyclical industries like the Semiconductor industry. They are cyclical by definition for a reason. SK Hynix is spending $38 billion on Fabs that to build more HBM. Some of the U.S. bans on Chinese tech actually will create more bottlenecks. All of this could increase the cost of compute and artificially inflate capex via delays and the added bottleneck costs. Even as the actual value of the tech is not being seen on the business level like you’d hope to see.

This Time It’s Different

I have been bombarded by AI boosting on social media for the last three years at disproportionate levels to pre GPT era times. So frankly, these "this time is different" arguments are really annoying and don’t do macro economics any justice. In a bubble, it’s really normal for people to become irrationally optimistic and abandon traditional valuation rules and believe old economic laws no longer apply. Reversion to the mean is like gravity, it’s not an opinion. That the mainstream media has been trying to brainwash everyone always talking about how revolutionary Generative AI is, to directly benefit the financial elite in various ways is fairly dystopian and undemocratic.

Mega Corps are Embracing Debt

Indeed hyperscalers rushing to do offerings, bond offerings and finding it not so difficult to go into debt and find credit is yet another sign of the AI bubble. A lot of this capital from the debt is just juicing the whole system. Whether that’s to help to pay for TSMC and HBM fabs or build datacenters to accelerate Cloud computing growth.

Amazon, Alphabet, Meta, and Oracle had issued about $194 billion of bonds in 2026 through July 7. Alphabet's current deal could add as much as $25 billion.

The Capex race is creating way more centralization on an already centralized U.S. equity market. The concentration of the NASDAQ 100 or S&P 500 in just a few names is itself a sign of a gigantic bubble. This capex extremism won’t end well, because it can’t. It’s not a sustainable practice. The energy grid, water infrastructure and climate risks can’t even entertain as many datacenters as they hope or plan to build. Greed is pushing extraordinary measures in bubble-like euphoria.

The Buffet Indicator

The ratio of market capitalization to GDP is also known as the Buffet Indicator. Not topically as common as the Shiller ratio but interesting nonetheless. It’s currently at around 2.34. The long-term mean going back to 1928 is closer to the level of 0.85. Roughly speaking, at or below 100% would be considered normal.

Buffett Indicator (U.S. Total Stock Market Capitalization to Gross Domestic Product).

Valuations are getting really insane in the AI bubble, especially in the private markets often not correlated with revenue growth in any meaningful way. Sometimes not even correlated to existing products. A lot of stellar AI labs don’t have products. The thing is in the real world that’s just not sustainable.

I’m no economists but there’s dozens to hundreds of indictor’s we are in an extreme market bubble caused by AI. Generated by AI, if you will. The runaway accelerating demand for compute benefits the top one percent in American wealth. But like the rise of Bitcoin or other schemes, I believe it’s more like mass fraud than a new paradigm. Of course I may be in the minority with my levels of skepticism, but I’m just a realist. This is not a conspiracy theory but living on an internet that’s clearly deceptive is getting difficult to accommodate.

AI has not been healthy to the labor market and won’t be healthy to inflation. There are structural problems in our economies and systems that AI will make worse, not better.

The M3 Bonanza

The U.S. Federal Reserve stopped publishing official M3 data in 2006, but historical charts from 1960 onward show M3 grew from roughly $298 billion to a peak of over $21.6 trillion by early 2022. The pandemic was the perfect excuse to print more money in a QE spectacle almost in preparation for something else. The AI bubble, is that something else. There’s a lot of liquidity and “cash on the sidelines” that can still be pumped into the AI bubble and equity markets. This is why the bubble won’t burst anytime soon as of mid 2026. A concentrated market is more easy to manipulate. Nvidia’s circular and vendor financing (which it does in self-interest) is the easiest and most transparent mechanism around this.

"Margin debt is the highest it's ever been, and there's a lot of margin debt you don't see because it's not called margin debt. It's called other things. Some hidden, some public. We see a lot of it, and it's high." - Jamie Dimon, CEO of JPMorgan

Margin Debt is at an all-time High

Nominal U.S. margin debt is troubling to me. There was an article in late May by Axios that stuck with me, but since then things have only gotten worse.

Thinking about this chart from John Hussman, showing margin debt relative to GDP spiking to all-time highs, with previous such instances seeming to foreshadow major market downturns. Again I’m not old enough to remember tech bubbles in much detail, but there’s a lot of AI bubble concerns.

Every bubble in history popped when margin debt hit 3% of GDP. (1929, 2000, 2008…) Today it’s at 4.5%. As you can imagine, trading with borrowed money — known on Wall Street as "margin" — can amplify both returns on the way up and losses if the market turns. Typically when even retail traders and consumers are taking out loans to invest in the stock market like we have seen in South Korea and Taiwan, it’s a sign of a major bubble.

Through the end of April, net margin debt hit more than 1.25% of U.S. market cap, near the highest level in records stretching back to 1997. Just three months later, it’s hit 4.5%.

👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. The macroeconomics of the AI bubble event is starting to worry me because it’s warping the real American economy and how debt and circular financing are being used to fund this Generative AI movement. AI products that aren’t really demonstrating exceptional value with the scale of diffusion you’d want to see for it to benefit workers, consumers and the future of work.

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