Despite massive investments and rapid revenue growth, concerns about the sustainability of the AI bubble loom large as companies struggle to turn a profit. Firms like Anthropic and OpenAI have seen astonishing revenue increases, yet questions linger about their long-term viability.
Anthropic’s revenue is increasing faster than many historical benchmarks — faster than Zoom’s during the pandemic, Google’s in the early 2000s, and even Standard Oil’s during the Gilded Age. Just two months ago, Anthropic’s annual run rate was $14 billion; now it has skyrocketed to $30 billion. Meanwhile, OpenAI reported a nearly 20 percent increase in its annualized revenue from December to February.
The landscape is changing rapidly. The percentage of American businesses subscribing to at least one AI tool has jumped from about a quarter at the beginning of 2025 to over half today. This surge indicates a growing reliance on AI technologies across various sectors. Google, Microsoft, and Amazon reported significant cloud revenue growth — 48 percent, 39 percent, and 24 percent respectively — largely driven by AI firms utilizing their services.
However, this growth comes with caveats. Sam Altman, CEO of OpenAI, expressed skepticism about the current enthusiasm: “Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes.” Azeem Azhar added that such rapid revenue growth “is absolutely not normal,” signaling potential instability.
Investment in AI has reached staggering levels — approximately $300 billion has been poured into chasing AI profitability. Yet many companies are still far from breaking even. Anthropic anticipates turning a profit by 2028 while OpenAI aims for 2030. This timeline raises critical questions: Will these projections hold up in an ever-evolving market?
Many companies are investing heavily in chips and infrastructure to meet anticipated demand for AI tools. Yet, this strategy could backfire if growth rates do not sustain themselves. Paul Kedrosky noted that market hype can lead to inflated demand, which then creates an illusion of necessity for increased supply.
Six months ago, experts compared the current state of the AI sector to historical bubbles like the railroad boom of the 1800s or the dot-com bubble of the ’90s. The parallels are striking — rapid innovation paired with equally rapid speculation often leads to unsustainable practices.
The sustainability of current growth rates for AI companies remains unclear. As companies grapple with profitability amidst soaring expectations, stakeholders will be watching closely.
