Is the AI Bubble About to Burst? – DW – 07/11/2025
Recent enthusiasm surrounding artificial intelligence is facing increasing scrutiny as concerns mount over its practical limitations and financial sustainability. While AI applications like ChatGPT have gained widespread use, experts are questioning whether current investment levels are justified by actual returns, leading to speculation about a potential market correction – or even a burst bubble.
A key weakness of current AI systems is their tendency to “hallucinate,” generating plausible but factually incorrect information. Reliability remains a significant issue, wiht autonomous agents successfully completing tasks only about a third of the time. Carl Frey, an expert in the field, emphasizes the need for continuous learning, stating, “Unlike a practitioner who learns on the job, pre-trained AI systems do not improve through experience. We need continuous learning and models that adapt to changing circumstances.”
The disparity between high expectations and business realities is beginning to impact investor confidence.Venture capital deals involving private AI companies decreased by 22 percent in the third quarter of the year. Economist Stuart Mills of the London School of Economics expressed concern over the scale of investment relative to revenue generated, telling DW, “What disturbs me is the magnitude of the investment compared to the revenue generated by AI.”
OpenAI, a market leader, generated $3.7 billion in revenue in the past year, while incurring operating expenses of up to $9 billion. The company projects revenue of approximately $13 billion for the current year, but anticipates spending a staggering $129 billion by 2029.
Julien Garran, a partner at MacroStrategy Partnership, argues the current influx of capital into AI surpasses previous speculative bubbles. He estimates it is indeed “17 times bigger than the dot-com bubble burst.”
Recent financial reports from major technology companies have offered a mixed picture. While Palatir’s third-quarter revenue increased by 63 percent, its share price fell 7 percent following the announcement. Similarly, positive AI-related results from AMD and Meta were tempered by market anxieties regarding long-term sustainability.This disconnect between growth and underlying fundamentals is a key concern for Mills, who observes a widening gap between AI’s promises and its actual market delivery.
Gary Marcus, a professor of psychology and neuroscience at New York University, believes manny generative AI companies are substantially overvalued. He predicts a collapse, potentially imminent, stating, “With the exception of Nvidia, which is selling in droves, most generative AI companies are wildly overvalued…The fundamentals, both technical and economic, do not make sense.”
Though, not all experts foresee a catastrophic outcome. Sarah Hoffman,director of AI Thoght leadership at AlphaSense,anticipates a “market correction” rather than a complete “cataclysmic bubble burst.” She suggests that corporate investment will become more focused, shifting from “big promises to clear evidence of the effects” of AI offerings, prioritizing “projects [that] generate measurable returns.”