AI is not a bubble.Lazy AI bears point to $NVIDIA(

AI is not a bubble.

Lazy AI bears point to $NVIDIA(NVDA.US)'s market cap and through PTSD, claim it resembles $Cisco(CSCO.US) in March 2000.

However, any useful bearish analysis should look at what actually made the 1990s market a bubble from a macro sense, and whether those conditions exist today.

I now refer you to the attached chart.

In the late 1990s the two lines veered apart. Tech investment went vertical toward ~4.5% of GDP, while the economy-wide profit share rolled over from its 1997 high and fell hard into 2000.

Investment surged while profitability eroded...bubble!

Today, the lines rise in tandem.

Tech investment has pushed to roughly 4.9% of GDP, above the dotcom peak and climbing more steeply, while pre-tax corporate profits sit near 14% of GDP.

Meanwhile leverage has (mostly) stayed contained and the US current account deficit is shrinking. However, bears point to record levels of investment in isolation, choosing to ignore the growing profitability in addition.

Are they dumb, or are they ignorant?

Probably both.

In the run up to March 2000, share prices rose and multiples exploded. The market paid more and more for each dollar of invisible earnings.

This time, forward P/Es have barely moved even as share prices rocketed, because earnings expectations rose alongside them. For example, the Nasdaq 100 trades around 23x forward earnings, near its own 10Y average versus ~60x in March 2000.

But...but....the market is so concentrated!! 1! 1!

Yes, the ten largest S&P 500 companies account for ~40% of the index, above the dotcom peak.

But those ten companies contribute around 30% of total market earnings, compared to under 20% in 2000, and trade at roughly a 50% premium to the rest of the market against a premium north of 100% at the prior peak.

Now, bears will say: "If the rally is earnings driven, everything depends on whether the earnings persist!"

Correct.

But unfortunately for the bears, this is where things get uncomfortable.

AI type names have added on the order of $27 trillion in market value since late 2022, up from roughly $19 trillion just seven months earlier. Set that against any weak attempt to discount the additional profit streams AI can plausibly generate for US companies (estimates cluster in the trillions) and the market has capitalised a multiple of the realistic prize.

Not all of that $27 trillion is AI (the hyperscalers run enormous non-AI businesses), and more aggressive assumptions on adoption and productivity can lift the number.

But closing the gap requires increasingly heroic assumptions:

- that recent shifts in earnings shares are highly persistent

- that the boom's suppliers capture an outsized slice of AI's total economic gains

- that the economy-wide profit share keeps climbing indefinitely

Alright, cool. But what about all the circular financing?!

- Nvidia has committed tens of billions to OpenAI while remaining its primary chip supplier

- OpenAI has signed a cloud commitment with $Oracle(ORCL.US) reported around $300B

- Oracle in turn buys from Nvidia

- $Microsoft(MSFT.US) is simultaneously OpenAI's largest investor and one of its largest vendors

True, this somewhat resembles the dotcom vendor financing where Cisco booked loans to cash stricken carriers as revenue (roughly a tenth of sales at the peak), much of it later written off.

However, today's arrangements are mostly equity stakes in counterparties with genuinely fast growing revenue rather than disguised loans to fund purchases, and Nvidia has lately been unwinding parts of its ecosystem book.

And according to analyst reports, even the AI labs like Anthropic have now turned profitable. A feat many thought would be impossible only a year ago.

Personally, I treat this circularity as risk rather than a point to build a bear case around since it's all ultimately leading to greater earnings across the board. Even for fronteir labs. Shock!

This then leaves the one key question:

Will barriers to entry protect today's profits from erosion?

This entirely depends on each company's position in the AI supply chain.

- At the model layer, barriers are relatively fragile where frontier models will almost certainly converge longer-term, and open source alternatives have the ability to reset price floors. However, AI soverignty will ultimately result in the likes of OpenAI/Anthropic winning.

- At the hyperscaler layer, $Amazon(AMZN.US), $Alphabet(GOOGL.US), $Meta Platforms(META.US), and $Microsoft(MSFT.US) are set to spend (currently) $750B for 2026 AI capex where falling behind is not an option. These companies are led by people smarter than you or I - do you think they'll risk their entire business collapsing for AI? No. In fact, you can already see that AI is boosting their earnings measurably in recent earnings.

- Going further down, you've got irreplaceable companies such as $ASML(ASML.US) (EUV machines), $Taiwan Semiconductor(TSM.US) (CoWoS packaging), and HBM with $Micron Tech(MU.US), SK Hynix and Samsung who are gated by long qualification cycles and multi year LTAs where demand > supply up to the 2030's.

The risk of a 2000 style valuation bubble is massively lower than the bearish consensus believes.

The world is revolving around AI, and that'll continue for the forseeable future.