AI’s Growth Meets Costs, Scale And Bottlenecks

International | 1:47 PM

Artificial intelligence is the most significant change to humanity in the 21st Century but the complexity, scale and needs for the technology create both opportunities and risks.

• Bubbles past and present, how the media handles the narrative
• Gen AI collides with national security and corporate imperatives
• How the adoption of AI is progressing and what are the fiscal benefits 
• Funding the biggest tech revolution in history 
• Constraints around infrastructure for potential winners
• Challenges for investors, juggling the narrative versus the facts

By Danielle Ecuyer

Framing the central tension

“Two things can be true at the same time: a) the data centers to power AI could be as economically worthwhile an investment as railroads, and b) we could still experience at least one stock market crash along the way to its general adoption."

[historian and economic commentator Niall Ferguson]

One’s memory often delivers flawed historical reality, so gleaning from personal experience is potentially fraught with erroneous signals.

Maybe it is investing muscle memory around the turn of the century Dotcom crash that brings forth a plethora of concerns, anxieties and ‘bubble’ narratives around AI and the associated infrastructure spend in 2025?

As noted by US advisory firm Carson Group, there has been so much talk about the “AI Bubble” that there are now articles on the “bubble in articles about the AI bubble”.

Bubblicious, if it wasn’t such an important topic for both investors, governments and companies.

Lessons from the Dot-Com Era according to ChatGPT

In the years leading up to the dot-com crash, mainstream media outlets were largely swept up in the euphoria of the internet age, celebrating innovation while downplaying risk.

Between 1994 and 1998, publications such as Wired, Forbes and BusinessWeek painted a techno-utopian vision of the “New Economy”, where traditional valuation metrics no longer applied. Analyses of New York Times and Wall Street Journal archives from that period show more than 80% of coverage on internet stocks carried a positive or neutral tone.

It wasn’t until 1998, following the Asian Financial Crisis and the collapse of Long-Term Capital Management, that scepticism began to creep into the financial press. Barron’s was one of the first to warn of “The Internet Bubble”, highlighting start-ups with no profits and inflated market capitalisations.

Yet, these early warnings were drowned out by an avalanche of bullish commentary, as cable business networks and glossy magazines continued to glorify tech founders and IPO millionaires.

Meanwhile, the Federal Reserve’s policy stance added fuel to the fire. After cutting rates aggressively in late 1998 to stabilise markets during the crisis caused by Long Term Capital Management's demise , the Fed’s easy-money environment encouraged risk-taking and speculative inflows into technology stocks.

The liquidity surge helped push the Nasdaq up more than 80% in 1999 alone. When the Fed reversed course, hiking rates six times between June 1999 and May 2000 to contain inflation and curb exuberance, the tide quickly turned. The same cheap capital that had inflated valuations began to dry up, exposing the fragility of profitless tech ventures.

By 1999, valuations had reached dizzying heights, but even then the media’s cautionary notes remained rare.

A 2002 Journal of Communication study found fewer than 10% of technology-related stories adopted a negative or cautionary tone that year. It wasn’t until early 2000 —just as the Nasdaq reached its all-time high— that major outlets like The Economist, The Wall Street Journal and The New York Times began openly questioning whether the frenzy had gone too far.

Headlines such as “How High Can Tech Go?” and “When Will the Bubble Burst?” reflected a shift from hype to hesitation, but the warnings arrived only months before the crash.

Subsequent research from Columbia Journalism Review and Harvard’s Shorenstein Center found that by early 2000, nearly half of technology-market coverage had turned negative, a dramatic reversal that coincided with, rather than anticipated, the bursting of the bubble.

The lesson was clear: far from acting as an early warning system, the media largely mirrored investor sentiment, amplifying optimism until it collapsed under its own weight. And while journalists were slow to sound the alarm, the Fed’s pivot from accommodative to tightening policy provided the spark that pricked the bubble.

Today, as headlines once again oscillate between the promise and peril of artificial intelligence, the dot-com era remains a cautionary reminder of how liquidity, sentiment and media narratives can converge to inflate, and then unravel a market mania.

Today’s media cycle and bubble narratives

In contrast, in this present cycle the media, US and notably Australian flagship publications are positively tripping over themselves to quote the bears and the naysayers.

The latest have transcended everything from Michael Burry’s apparent shorts on Nvidia and Palantir (apparent because the data he tweeted on options activity was from the rear-view mirror) and Bank of America’s Michael Hartnett who is pointing to Big Tech corporate bond issuance in the last week as signs capex spending for Big Tech has transcended past free cash flows.

A concern around all bubbles is that spend is being debt funded that cannot be financed, i.e. insufficient cash flow is generated and the returns on AI-related spend do not come forth from revenue generation with sufficient margins and a failure for earnings growth to materialise.

All the while the opportunity cost of not doing enough hangs potentially like the Sword of Damocles over Big Tech if they do not invest.

Mark Zuckerberg was quoted as saying in September “If we end up misspending a couple of hundred billion dollars, I think that is going to be very unfortunate, obviously … But what I’d say is I actually think the risk is higher on the other side”.

Larry Page, co-founder of Google, stated, “I’m willing to go bankrupt rather than lose this race”.

It is not a stretch that America’s Big Tech companies see AI as an existential risk to their existence.

As a result, they are all investing heavily and for some, increasingly, beyond their potential payback cash flow generation to be part of the AI ‘revolution’.

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