It’s common to compare each new technology revolution to the one that preceded it.
After all, history often provides us with useful benchmarks. If the internet took this long to spread or smartphones grew at that pace, it’s reasonable to assume that the next breakthrough will follow a similar path.
In other words, history has become our shorthand for predicting the future.
But what if artificial intelligence isn’t following that script?
According to this week’s chart…
It isn’t.
Faster Than Anything Before It
Today’s chart comes from a fascinating new report by Exponential View, the research firm founded by technology analyst Azeem Azhar.
The report tackles a surprisingly difficult question.
How much are customers actually spending on artificial intelligence?
That’s harder to answer than you might think.
You see, most AI companies don’t break out their AI revenue. Many of the biggest AI labs are privately held, and the same dollar often flows through several companies before reaching the end customer.
To solve that problem, Exponential View’s researchers built a bottom-up model covering more than 1,000 companies. They traced AI spending through application developers, model providers and cloud infrastructure while carefully removing double counting.
Their goal was to measure real customer demand.
That’s what makes today’s chart so interesting. Rather than comparing stock prices or user growth, it compares inflation-adjusted revenue growth during the first three years of four relatively recent major technology waves…
The internet, mobile phone, cloud computing and generative AI.
And as you can see, the difference is shocking.
According to Exponential View, AI revenue is growing roughly 3X faster than any of those previous technology revolutions did over the same period.
This helps explain why so many companies are racing to build AI infrastructure.
The report estimates that the generative AI economy has already generated roughly $110 billion in revenue over the past 12 months. Based on its current pace, that annualized run rate has already climbed to about $175 billion.
To me, that’s the real story of this chart.
Hyperscalers continue to announce enormous data centers. Utilities are still scrambling to add electricity. And chipmakers are struggling to keep up with demand.
Meanwhile, many investors have started wondering whether this has become another technology bubble.
But this chart tells us that Wall Street might be making the mistake of thinking about AI as if it’s another internet or cloud computing cycle.
And the report argues that’s a dangerous assumption.
If AI adoption is accelerating 3X faster than previous technology waves, using those older models could underestimate future demand, infrastructure needs and even how quickly companies recover their massive AI investments.
The report goes even further.
It argues that this demand has already created a new compute supercycle, requiring roughly 10X more computing power, larger data centers, new sources of electricity and growing infrastructure backlogs as suppliers struggle to keep pace.
That doesn’t mean every AI investment is bound to succeed. In fact, the authors identify one enormous question still hanging over the industry.
Can AI become cheap enough to create the volume of demand needed to justify all of this spending?
That’s the trillion-dollar question we’ll all be monitoring over the next several years.
Here’s My Take
It’s tempting to compare today’s AI boom with previous technology revolutions. But history can become a trap if we’re trying to understand something fundamentally different.
Yes, there is a massive infrastructure buildout taking place around artificial intelligence.
Today’s chart helps explain why.
And if AI demand really is happening 3X faster than previous technology waves, then today’s spending could look far less outlandish in just a few years.
In fact, it could simply prove to be the price of keeping up.
Regards,
Ian King
Chief Strategist, Banyan Hill Publishing
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