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It Looks Like A Bubble, It Feels Like A Bubble, But It Isn't

  //stocks-investing.news-articles.net/content/202 .. -bubble-it-feels-like-a-bubble-but-it-isn-t.html
  Published in Stocks and Investing on Saturday, October 18th 2025 at 13:20 GMT by Seeking Alpha

The Calm After the Frenzy: Why AI Hype Isn't a Bubble (Yet)

The recent surge in investment and attention surrounding artificial intelligence has prompted comparisons to past speculative bubbles – dot-com, cryptocurrency, even tulip mania. A Seeking Alpha article by Michael Bagel, published on May 15, 2024, titled "It Looks Like a Bubble, It Feels Like a Bubble, But It Isn’t," directly addresses this sentiment, arguing that while exuberance is palpable, the current AI landscape differs significantly from historical bubble formations and doesn't warrant immediate panic.

Bagel begins by acknowledging the surface-level similarities. The rapid price appreciation of AI-related stocks, particularly those associated with generative AI models like OpenAI’s GPT series, mirrors the inflated valuations seen in previous speculative periods. The narrative surrounding AI – its potential to revolutionize industries and fundamentally alter society – echoes the utopian promises made during the dot-com boom. Furthermore, a significant portion of investment is driven by retail investors fueled by social media hype and Fear Of Missing Out (FOMO), a common characteristic of bubble markets.

However, Bagel contends that crucial distinctions separate this AI fervor from classic bubbles. The most critical difference lies in the underlying technology's demonstrable utility and tangible progress. Unlike many dot-com companies with unproven business models or cryptocurrencies lacking intrinsic value, AI is already delivering real-world results across diverse sectors. He points to advancements in areas like drug discovery, customer service automation, code generation, and content creation as evidence of this practical application. These aren't just theoretical possibilities; they are actively impacting businesses and generating revenue.

The article emphasizes that the current investment frenzy is largely concentrated within a relatively small subset of AI-related companies – primarily those directly involved in developing or deploying large language models (LLMs). While these companies have experienced explosive growth, Bagel argues this reflects genuine innovation and increasing demand rather than purely speculative behavior. He highlights Nvidia (NVDA) as a prime example. Nvidia’s stock price has soared due to its dominance in providing the specialized GPUs essential for training and running AI models. This isn't simply hype; it's driven by a fundamental need within the burgeoning AI ecosystem. [Seeking Alpha provides an overview of Nvidia's recent performance here: https://seekingalpha.com/company/134256/nvidia/]

Bagel also challenges the notion that current valuations are entirely detached from reality. While some companies may be overvalued, he suggests that the potential for future growth in AI is so significant that existing price-to-earnings (P/E) ratios, while high, might not be unsustainable. He cautions against a blanket dismissal of all AI investments as being inherently overpriced, advocating instead for careful analysis of individual company fundamentals and long-term prospects.

The article further differentiates the current situation from past bubbles by noting the involvement of established institutional investors alongside retail participation. While retail FOMO undoubtedly contributes to volatility, significant investment from venture capital firms and hedge funds indicates a belief in the long-term viability of AI technologies. These institutions typically conduct more rigorous due diligence than individual retail investors, suggesting a degree of fundamental support for the sector.

Bagel acknowledges that risks remain. He points to potential regulatory hurdles, ethical concerns surrounding AI bias and misuse, and the possibility of technological breakthroughs rendering current models obsolete as factors that could impact future growth. The article also mentions the "AI winter" scenario – a period of reduced investment and disillusionment following an initial wave of hype – as a possible outcome if expectations aren't met or progress stalls. [The concept of AI winters is explored in detail by MIT Technology Review here: https://www.technologyreview.com/2023/11/08/1083496/the-ai-winter-is-coming/]

However, Bagel concludes that the current environment isn't a bubble destined for an inevitable burst. Instead, he describes it as a period of intense innovation and rapid adoption, characterized by high valuations but underpinned by genuine technological advancements and increasing real-world utility. He advises investors to approach AI investments with caution, conducting thorough research and focusing on companies with strong fundamentals and sustainable competitive advantages, rather than succumbing to the allure of quick riches. The article suggests that while a correction is always possible, it's more likely to be a period of consolidation and recalibration rather than a catastrophic collapse akin to previous market bubbles. The key takeaway is that AI represents a transformative technology with long-term potential, and dismissing it as a mere bubble risks missing out on significant opportunities.