A New Development in K-Shaped Economics… Why Luc Langeaux Says the Iran War Will Expand the K… A New Hole Emerges Within AI Itself… Beware of Growing Risk in Private Credit… And What It All Tells Us About the Future of AI
The upper arm of the ‘K’ represents… the top 20% of high-income households – but nearly half of them can walk on eggshells…
This line comes from A luck Article from earlier this week. It points to something quietly changing beneath the surface of what we thought we understood about who is financially well off today.
Here’s the short version: Today’s K-shaped economy, where asset owners prosper while wage-dependent households struggle, has evolved into a new rift – one that is shaping up inside “Who own” themselves.
Back to luck:
The wealthy who are exposed to financial risk are “high-income earners whose lack of budget and wasteful spending have led to excessive leverage and exposure…
While they appear to be doing well on the outside, they are only one step away from real financial trouble.
according to luckNow those wealthy enough to be insulated from this “real financial problem” have a new name – “safe elites.”
Now, there is a fascinating parallel that occurs in today’s stock market. But before we explore that, let’s start with the market equivalent of a K-section…
Artificial intelligence versus everything else.
Get ready for a K-shaped stock market expansion
A long time ago digest Readers know this story well.
On one side of the market, we have the stocks of “yesterday’s economy” (except oil, more recently) – companies that have not been able to keep up with rapid technological progress.
On the other side, we have AI and the companies that support it, riding upward on the back of massive capital investment and massive profit growth.
To illustrate the performance gap, the chart below shows the equal-weighted S&P 500 index up about 40% over the past two years, while the S&P 500 is up about 40% over the past two years. GlobalX Artificial Intelligence and Technology ETF (AIQ) It rose more than 100% during the same period.
To be clear, “non-AI” stocks haven’t done badly — they’ve just lagged behind. This dichotomy has defined this market.
According to hypergrowth expert Luc Lango, editor Innovation investorThis delay will not disappear. If anything, he believes the current overall uncertainty will make the matter clearer:
Yes, the war will end. But no, everything will not go back to “normal.”
The consumer, who is already suffering…faces the cost of sustainable energy and a more constrained credit environment for a longer period than pre-war projections suggested.
These are real headwinds for real companies. The broad market faces real pressure from the effects of the ongoing war that do not disappear on the day of the ceasefire.
But Locke says the story is different for the AI sector.
Hyperscaler capex decisions are made on 5-10 year return horizons – dismal consumer surveys notwithstanding…
Microsoft and Google aren’t cutting AI data center budgets because American workers haven’t gotten a pay raise recently…
Brent crude settling at $75 instead of $65 will not affect Nvidia’s $1 trillion in confirmed orders.
Luke concludes:
Sophisticated capital with perfect industry information makes commitments on the scale of a contract (AI) in the middle of a war.
This is the clear preference of people who know more than the overall hype suggests…
Buy AI infrastructure in chop. Be careful in the broad consumer exposed market.
Looking back, the takeaway is familiar – but important…
We still have a K-shaped market. Based on Locke’s analysis, today’s macro uncertainty will likely reinforce this outperformance of technology versus “the rest.”
But here’s the new wrinkle…
Even within AI, a new division is taking shape.
Let’s get back to that luck Framing a moment…
Within the top tier of the economy, we have the “safe elites” – households with strong balance sheets, low debt, and real financial resilience. However, there are also high-income earners who He looks They are financially healthy but “just one step away from real financial problems.”
There is a similar dynamic occurring within artificial intelligence.
On the “safe elite” side are the companies at the center of building AI – chip makers, data center suppliers, and infrastructure players. These companies are seeing huge and clear demand. Commands are locked. Capital is committed. Revenues are increasing.
Whether direct-to-consumer AI products make a dime of profit will not matter to the “safe elite” revenues over the next three to five years, as scalers pour billions into launching AI infrastructure.
But take one step away from this essence and the picture begins to change.
How much are people willing to pay for AI?
This is a question that the market is now starting to ask seriously.
Let’s start with the obvious…
The purpose of AI infrastructure is not just to “exist” – it is to power applications that people and businesses are willing to pay for. But this is where the story starts to fall apart.
The part of AI that consumers actually use – the part they are expected to pay for – is the software. Models. Interfaces. Tools that help users write, design, analyze, and automate.
But while the physical infrastructure of AI is generating real profits today, the software that runs on top of it faces economic headwinds. The evidence is starting to pile up…
Since late October, iShares Expanded Technology Software ETF (Value added tax) Decreased by 30%.
At the same time, she loves companies sales force (Customer relationship management), working day (day) and ipath(road) Each suffered double-digit declines as investors reevaluated their place in the AI story.
What makes this shift notable is that, until very recently, many of these same companies were seen as primary beneficiaries of AI – not fringe players, but “top AI,” central to the trade.
Investors piled them alongside infrastructure names, assuming they would ride the same wave of demand and monetization.
This assumption cracks.
Axios A study by researchers from the Massachusetts Institute of Technology (MIT) examining hundreds of AI initiatives was recently highlighted. Their finding is that despite spending tens of billions of dollars, the vast majority of organizations have yet to see a tangible return.
This does not mean that artificial intelligence will not achieve success. But this means that the timeline – and the economics beyond the physical rollout of AI today – remain truly uncertain.
The evidence that tells us this is real private credit
Now, a true believer in software might say, “Jeff, the 30% decline in IGV is just froth coming out of the market. That doesn’t mean software isn’t a safe elite.”
justice.
So, let’s shift our focus away from stock prices to operating cash flows.
We will do this by looking at the private credit market. This is a corner of the financial system that we have been tracking in digest Along with the legendary investor Louis Navellier – which is worth understanding, because it is directly related to what happens in artificial intelligence programs.
Private credit, in simple terms, is lending that occurs outside traditional banks. Instead of the company borrowing from JPMorgan, it borrows from a private fund — often at higher interest rates, with fewer public disclosures and less liquidity for investors who put money into it.
For years, major private credit funds – incl Blue Owl Capital (owl), blackstone (BX) and Ares Management (Ares) – They poured billions into software companies, betting that steady subscription revenues would make them safe and reliable borrowers.
But in recent months, what some are calling the “as-a-service apocalypse” has cast doubt on the real winners and losers in AI.
Many of these software companies find that the actual cash flows from their AI products are not strong enough to cover their debt obligations. Customers are building their own tools, wondering about expensive software upgrades or simply not renewing. The numbers are alarming.
here Business insider:
The specter of AI disruption in the software sector could see private credit defaults rise to their highest level since the pandemic, Morgan Stanley said.
The default rate in direct lending could rise to 8%, strategists estimate, approaching the peak default rate seen during the pandemic.
They added that this trend will be largely driven by the disruptive effects of AI on software companies.
These cash flow pressures are spreading across the funds that have financed these companies, and investors are feeling the danger.
As we highlighted it yesterday digestSome trusts have initiated “gateway” withdrawals. In other words, investors who assumed their money would be accessible are now being told they may have to wait months or longer to get it back.
Lewis believes the worst is yet to come:
For the past year and a half, I have been warning people about one of the biggest risks to the financial system – a risk that has been hiding in plain sight.
Private credit.
Wall Street was able to weather some of the pressure, extending loans, restructuring terms, and pushing the problems a little further into the future. But this kind of “expand and pretend” strategy only works for so long.
Sooner or later, the market is forced to confront which assets are sound, which loans are undervalued, and which borrowers never made it through a tighter credit cycle.
I think the private credit market is approaching a real moment of truth.
Now, it’s not all bad. Lewis argues that money does not disappear in every crisis, but rather moves from weak balance sheets into high-quality, cash-rich, low-debt “fortress” stocks.
He’s just released a deep dive into the growing cracks in private credit that don’t just include details How to protect your wallet, but how to benefit This crisis is redirecting massive flows of capital through the financial system.
Bottom line: If you are a member of a trust with exposure to programs, I hope you make time to watch it.
Coming full circle
At the top of this digest, luck He described the financially vulnerable wealthy as “high-income earners whose lack of budget and wasteful spending have led to over-leverage and exposure…just one step away from real financial problems.”
The private credit funds that financed the AI software boom were, in their own way, lending to this exact file: companies that looked like stable, subscription-based companies on the outside… but were quietly burning through money and over-leveraging beneath the surface.
Today, both groups are in trouble: software borrowers who don’t generate enough revenue to repay their loans, and the money betting that they will.
So, just as we now have a new “safe elite” within the upper tier of households, we are seeing a similar division within AI itself. We see this in the strength of infrastructure names… the weakness of software… and the increasing pressures in the private credit markets that have funded this growth.
It’s the same story, just appearing in different places.
This leaves us with a simple but important shift in how we think about this market…
We can no longer just “own AI” – and certainly not lend it blindly.
After all, in a K-shaped market, the difference between being among the “safe elite” versus everything else can have serious consequences for your investment portfolio.
One last thought before we go…
If the world is paying trillions to build AI… but the AI is struggling to repay its loans, at what point can we ask whether hyperscalers will see a real return on that investment?
Perhaps most troubling: What if the honest answer to the question “How much will the world actually pay for AI” turns out to be much less than investors currently assume?
I wish you a good evening,
Jeff Remsburg
