CoreWeave, the first AI startup to go public, faced disappointment from investors, closing its first day of trading with a market capitalization of $19 billion. This valuation mirrors the amount it raised as a private company in May 2024, almost triple its worth just five months earlier. The AI bubble seems to be nearing its peak, prompting concerns that it may soon burst, followed by a phase of reassessment, ultimately leading to AI-based business practices that generate profits rather than losses.
In January, the “DeepSeek Moment” pushed the AI bubble to the brink. AI entrepreneurs in the U.S. responded to a sudden and formidable Chinese competitor by advancing predictions about the imminent arrival of Artificial General Intelligence (AGI). Some also doubled down on exaggerated claims of AI’s transformative impact on businesses. Dario Amodei, CEO of Anthropic, for example, anticipated that in just 12 months, AI would be capable of writing “essentially all of the code,” a development that could displace millions of programmers.
However, according to Wired’s Steven Levy, who gained access to internal Anthropic meetings, Amodei sees the arrival of AGI as far more critical than cost-saving measures. Within a year, Anthropic and other companies may produce machines capable of surpassing Nobel laureates in intelligence. The expectation is that these AGIs will collaborate, potentially revolutionizing areas such as healthcare and extending human lifespans significantly.
Despite such visionary promises, the historical trajectory of AI remains rooted in the gradual evolution of computing. From the 1950s onward, marketing campaigns such as “Artificial Intelligence” and “Artificial General Intelligence” have masked the long-standing development of increasingly capable computers. This evolution—from scientific calculators to personal devices, and now AI—has been marked by cycles of overblown expectations followed by periods of disillusionment, before reaching practical stages of productivity.
Reflecting on earlier technology milestones, the IT moment in the late 1950s foreshadowed the rise of computers in business. By the 1960s, predictions like Moore’s Law emphasized the rapid increase in processing power. Likewise, the networking moment in the 1970s and Metcalfe’s Law promoted the growing importance of scale in computing, with networks becoming central to the development of AI and big data.
Today, AI’s market appeal continues to drive investments, though much of this is driven by marketing creativity. While the technology’s full impact remains to be seen, new research indicates that AI could transform how work is done in organizations, offering new ways to reimagine teamwork and management structures. As AI tools become integrated into daily business practices, organizations are urged to rethink their approach to both work and leadership.
AI enthusiasts might be at the peak of the bubble, but as with previous technology cycles, it could take another year or two before deflation hits. Regardless, the marketing campaign surrounding AGI promises to remain resilient, continuing to fuel the race for the next big breakthrough in AI.
