AI’s Double-Edged Sword: Tech Revolution or Market Bubble?

The past month has delivered a seismic shock to the global economy, with investors sending an unmistakable message to industries from software and wealth management to legal services and logistics: AI is coming for your business.

This warning comes amid a dramatic stock market slide that has swept across sectors as diverse as drug distribution, commercial property, and price comparison websites. The catalyst? The relentless release of increasingly powerful AI tools that are making once-farfetched predictions about white-collar job obsolescence suddenly seem plausible.

Carl Benedikt Frey, author of How Progress Ends and associate professor of AI and work at Oxford University, explains the investor mindset: “AI turns once-scarce expertise into output that’s cheaper, faster, and increasingly comparable, which compresses margins long before whole jobs disappear.”

The fears of widespread job losses reached fever pitch this week when AI entrepreneur Matt Shumer’s viral essay, “Something big is happening,” was viewed a staggering 80 million times on X. Shumer warns that new AI models will first target coding jobs and then “everything else,” comparing our current moment to February 2020—just before the COVID pandemic transformed the world.

But Shumer’s credibility has been questioned. He previously ignited the internet by announcing the release of the world’s “top open-source model,” which was later revealed to be not actually the best.

The market’s anxiety is reacting to cutting-edge models like Anthropic’s Claude Opus 4.6 and OpenAI’s GPT-5.3-Codex—significant improvements over already powerful AI products. However, the current climate is fueled by more than just technological advancement.

The so-called AI “hyperscalers”—the tech giants driving the AI revolution—collectively plan to spend an eye-watering $660 billion this year. This follows a year of colossal, often circular deals between the world’s biggest tech companies. Yet cracks are appearing in these numbers. Nvidia and OpenAI recently appeared to drop a $100 billion deal, replacing it with a smaller, as-yet-unknown commitment.

Here’s the fundamental problem: none of the AI model builders—not OpenAI, xAI, or Anthropic—have a clear path to the enormous revenue that would justify this spending. The entire global software sector is projected to generate just $780 billion in revenue this year.

The tension between these two narratives—AI as an unsustainable bubble versus AI as a destructive revolution in white-collar work—was on full display this week when shares in Google’s parent company Alphabet and Meta were affected by concerns about a spending bubble.

Investors are banking on these companies recouping their massive investments through millions of individuals and businesses paying for AI tools that promise to complete tasks with fewer people or in less time. In economic terms, they’re betting on a productivity boom.

Jason Borbora-Sheen, portfolio manager at investment firm Ninety One, notes: “The two themes are inherently linked but not necessarily contradictory.” Initially, investors backed the hyperscalers’ spending during the AI gold rush. Now concerns have shifted to cash burn and the sheer scale of investment needed to stay competitive.

While companies like British American Tobacco have cited AI in job-cutting plans this week, there hasn’t yet been wholesale disruption. Greg Thwaites, research director at the Resolution Foundation, says evidence of tangible AI job impact on large Western economies is “quite ambiguous so far.”

Not all white-collar work will be affected equally. Thwaites suggests AI might test the age-old capitalist concept of “creative destruction,” where entirely new jobs replace outdated ones. But will AI be different because the change has come so fast or because it will be good at absolutely everything?

Alvin Nguyen, an analyst at Forrester, argues that the market fears are based on sentiment rather than evidence: “It’s a kneejerk reaction. How true is it? There’s plenty of leaders who thought they could replace people with AI at the beginning. And I think one of the things being found out is that for a lot of cases, no, it hasn’t panned out.”

Aaron Rosenberg, partner at venture capital firm Radical Ventures and former head of strategy at Google’s AI unit DeepMind, believes the impact of AI is being underestimated in the long term but adoption will not be uniform. “History shows a repeated pattern of significant lag between a technology working in a lab and it permeating the wider economy,” he says.

Meanwhile, the AI industry is experiencing its own turbulence. High-profile tech workers are departing AI companies for various reasons—from boredom to AI doomerism to concerns over the prospect of adult content in ChatGPT.

As Borbora-Sheen succinctly puts it: “There is a strong winners versus losers dynamic.”

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