Stark warnings in the realm of AI development, investment | Cash Call | Andrew Wong

Anthropic chief executive Dario Amodei has delivered a warning that the AI market may not want to hear: The industry needs to slow down.

His comments come at a particularly sensitive time for the sector, as concerns over the risks of increasingly powerful, self-improving AI systems are moving from the fringes of the technology community into mainstream investment discussions. AI researcher Jacob Coxon, who previously worked at OpenAI before joining Anthropic, has also raised serious concerns about the direction of the industry, arguing that the race among leading AI companies in the United States to develop increasingly autonomous and self-improving models could ultimately put human lives at risk.

For investors, the significance of these comments goes well beyond the debate over AI safety.

What is becoming increasingly important is that some of the industry’s own leading figures are beginning to acknowledge that the current pace of development may be difficult to sustain. Amodei has called for a slowdown, while OpenAI chief Sam Altman has indicated that the company does not plan to pursue an initial public offering this year. Elon Musk has also acknowledged that the pace of AI development should moderate. This is precisely why the AI bubble argument deserves to be taken seriously.

I have repeatedly pointed out that artificial intelligence is showing clear characteristics of a bubble. That does not mean AI has no future, nor does it mean the technology will fail to transform the global economy. Quite the opposite. The problem is that markets have a tendency to price the future too aggressively, particularly when a revolutionary technology is involved.

The real question is therefore not whether AI will change the world. It is whether the world can absorb the economic, financial, and physical costs of AI developing at the speed currently being priced into valuations. The electricity market is perhaps the clearest warning sign.

The explosive growth of AI data centers is placing unprecedented pressure on power grids, forcing governments and companies around the world to accelerate investment in electricity generation and transmission infrastructure. Nuclear power, gas-fired generation, and other sources of electricity are increasingly being brought into the discussion simply because the AI industry requires enormous amounts of reliable power.

But there is a catch. Building power plants does not automatically solve the problem. Grid capacity, transmission infrastructure, permitting, construction timelines, and environmental constraints all create bottlenecks. In other words, AI may be advancing at semiconductor speed, while the physical infrastructure required to support it is moving at infrastructure speed.

That mismatch could become one of the biggest constraints on the next phase of the AI boom. And then there is the labor market.

The International Monetary Fund estimates that around 40 percent of jobs globally are exposed to AI, with the figure rising to approximately 60 percent in advanced economies. Some workers will undoubtedly benefit from higher productivity and AI-assisted workflows. But the other side of the equation is far less comfortable: weaker hiring, downward pressure on wages and, in some industries, outright job displacement.

This creates a paradox that investors should not ignore. If AI dramatically increases corporate productivity but simultaneously reduces employment and household income, who ultimately becomes the consumer of the AI economy?

You cannot build a sustainable economic model simply by selling increasingly powerful AI services to companies while eroding the purchasing power of the workers and consumers who ultimately support the broader economy.

Therefore, while figures such as Jensen Huang continue to emphasize the enormous potential and benefits of AI, their views are inevitably influenced by the interests of their own companies and the performance of their share prices. By contrast, Jacob Coxon’s comments highlight the underlying risks and fundamental problems surrounding AI development far more directly. More importantly, his warnings could prove to be a catalyst for exposing the excesses of the current AI investment cycle and ultimately puncturing the AI bubble.

Andrew Wong is a veteran independent commentator

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