It is worth reading carefully, because it does not mean what it looks like. It
is not that artificial intelligence is used less. It is that customers found a way
to use the same thing for less money.
Where the decline comes from
Far cheaper models appeared, especially from China, capable of handling much of
the work for a fraction of the cost. And when a company gets similar results
paying much less, the first casualty is always the same:
pricing power.
That is what separates this signal from ordinary noise. A sector can survive
growing more slowly. What is much harder to survive is unit prices collapsing while
investment keeps climbing.
The arithmetic that worries
If revenue grows more slowly, the question gets uncomfortable: how do you
justify the hundreds of billions going into data centres, chips and new
infrastructure.
Some analysts already compare the gap between investment and sales to the
overspending in telecoms before the year 2000. The parallel has a limit — back
then fibre was laid that took a decade to use, while today capacity is occupied
almost as soon as it is switched on — but the underlying arithmetic is the same:
spending running ahead of revenue.
The other side, which is also real
This story has an honest counterweight. Demand for memory and chips is still
enormous, the most advanced processors remain effectively sold out, and slack is
not expected until 2028. Many companies keep expanding their projects.
In other words: the problem is not a lack of customers. It is
that those customers now want more efficient, cheaper models. It is a margin
problem, not a demand problem — which is worse than it sounds, because a demand
problem can be seen coming and a margin problem shows up directly in the
results.
The regulatory factor
On top of this come new regulations in the United States and Europe, which make
the most powerful models more expensive and slower to deploy. The practical effect
is to push many companies toward lower-cost alternatives — exactly the same
direction as the price pressure.
The battle ahead
The real competition is no longer who builds the best artificial intelligence.
It is who manages to make money from it. If customers stop paying
premium prices, the sector's next great challenge will not be technological: it
will be financial.
And that is the figure likely to define the next winners and losers, far more
than any new model announcement.
Frequently asked questions
Is AI usage actually falling?
No. What fell roughly 20% from its late-May peak is token spending — the money companies pay to use the models. Usage is not down: customers found ways to do the same thing for less, largely with far cheaper Chinese models.
Why is a margin problem worse than a demand problem?
Because a demand problem can be seen coming, while a margin problem shows up straight in the results. Memory and chip demand is still enormous and the most advanced units are still sold out; what is eroding is the pricing power of whoever sells the models.
How does this compare with telecom in 2000?
The underlying arithmetic is the same: spending running ahead of revenue. The parallel has a real limit — back then fiber was laid that took a decade to use, while today capacity is filled as soon as it is switched on — but the gap between investment and sales rings the same bell.
