The AI Money Carousel

Everybody is talking about AI. Your neighbour mentions it at dinner. Your barber has an opinion. Politicians who struggle to send an email are debating its regulation in parliament. Artificial intelligence has become the defining conversation of our time — and most people talking about it have no idea what it actually does.

But here is what concerns me. Underneath the breathless excitement, underneath the record stock prices and the trillion-dollar announcements, something is quietly building. A hidden pressure. The kind that doesn't make noise until the moment it does — and by then, it's too late.

I have been investing for over two decades. My first serious investment was a Maltese government bond in 2012 — 4.85% per year, nothing glamorous. I sold it three years later with a 50% capital gain. That taught me something I have never forgotten: patience and independent thinking beat the crowd almost every time. Since then I have invested through bull markets and bear markets, through euphoria and panic, and through one humbling truth — that emotions are the most expensive thing in any portfolio. I have lost money because of emotion. Real money. Which is why I now write everything down, study history obsessively, and analyse before I act. I have a degree in history and international relations, and I genuinely believe it is one of the most useful things I bring to investing. Not because history repeats. It doesn't. But because it rhymes. And right now, I am hearing a very familiar tune.

The dot-com crash of 2000 to 2002 — when for the first time in nearly a decade the charts didn't just dip but collapsed — feels like ancient history to most investors today. People lost fortunes. Companies worth billions on a Tuesday were worth nothing by Friday.

The most successful companies in the world all have one thing in common

Look at the top of the S&P 500 today. The Magnificent 7 — Microsoft, Apple, Nvidia, Alphabet, Amazon, Meta and Tesla — account for over 35% of the entire index. If you own an S&P 500 tracker, more than a third of your money is riding on seven companies. All of them are betting heavily on AI. All of them are doing extraordinarily well — for now.

But look closer. Look at what these companies are actually doing with their money, and a strange picture begins to emerge.

Microsoft invests billions into OpenAI. OpenAI runs on Microsoft's Azure cloud — so Microsoft profits from its own investment. Nvidia sells the chips that power OpenAI's models. OpenAI has now taken a stake in AMD, a Nvidia competitor — while Nvidia itself has pledged $100 billion back into OpenAI. Oracle's entire future revenue growth is tied to a $300 billion cloud contract with OpenAI. Amazon, Google and Meta are all building data centres at a scale never seen before, buying chips from the same small group of suppliers who depend on these same giants as customers.

The money is moving. But it is largely moving in a circle.

What is circular investing — and why does it matter?

Think of it this way. Imagine five friends who agree to buy dinner for each other every night. On paper, they each spend and earn the same amount. They look busy, they look prosperous — but no new wealth is actually being created. The moment one of them loses their job and can no longer pay, the whole arrangement collapses.

Where is the real customer?

The revenue gap nobody talks about

The numbers tell a sobering story. AI companies will need $2 trillion in annual revenue by 2030 to justify the infrastructure they are currently building — and at today's projections, they are short by $800 billion. OpenAI, the company at the centre of all of this, is expected to lose $5 billion this year alone — despite commitments worth many times its projected revenue.

The combined free cash flow of Amazon, Google, Meta and Microsoft is projected to shrink by 43% between 2024 and early 2026 — not because the businesses are failing, but because capital expenditure on AI infrastructure is consuming it faster than it can be replenished. Goldman Sachs expects Big Tech to spend over $1 trillion on chips and data centres over the next five years. Where does the revenue to justify this come from?

Have we been here before?

The comparison to the dot-com bubble is imperfect — but instructive. And I want to be transparent about why I keep returning to history. I studied it formally — international relations and history — and it shaped how I see almost everything, including markets. The patterns of human behaviour around money are remarkably consistent across centuries. The euphoria, the denial, the rationalisation, the panic. When I look at the AI boom today I am not just running numbers. I am recognising a feeling. I have felt this feeling before. Most people currently invested in AI have not.

The bull case is real and I do not dismiss it. AI may well be the most significant technological revolution since the industrial revolution. But history does not ask whether the technology is real. It asks whether the price is right. And whether the money flowing through the system represents genuine new value — or the same dollars moving between the same hands, getting counted again and again.

What this means for your portfolio

I am not predicting a crash. Nobody can. But I am suggesting that the moment to think about this is before the music stops — not after.

I know what courage in markets actually feels like — not the bravado of riding a bull run, but the quiet conviction of buying when everyone else is selling. In the 2022 correction, when sentiment was at its worst and valuations had collapsed, I invested in Amazon, Nvidia and the S&P 500. Nvidia alone went up 800% from my entry point. Not because I am exceptional — but because lower valuations create better odds. That principle works in every market cycle, without exception. The inverse is equally true. High valuations driven by circular momentum rather than real earnings create poor odds. That is where we are today.

I speak to friends regularly who are buying every small dip — treating a 1% or 2% correction as a buying opportunity, adding more of the same concentrated positions. I understand the instinct completely. It has worked, consistently, for three years. But I find myself asking a quiet question: do they understand what they actually own? Do they know that more than a third of their S&P 500 tracker is riding on seven companies whose balance sheets are increasingly tied to each other? Are they investing with conviction — or following a trend that has not yet ended? There is a difference. And that difference matters enormously when the trend eventually does.

The AI revolution is real. The bubble may also be real. Both things can be true at the same time.

The question worth asking yourself today is a simple one: if the circle breaks, where are you standing?