AI's Real Potential: Cutting Through the Hype and Local Bubbles

Published Date : 27/08/2025 

While AI is undeniably transforming industries and investor portfolios, the current hype around AI has raised concerns about overvaluation and financial risks, particularly for newer startups. 

AI’s growing dominance in the world, whether it be reshaping industries’ workflows or influencing investor portfolios, is redefining how society and economies evolve. Of course, the hype and buzz around AI have been and are hard to ignore, but the question is, does this hype often overshadow the real challenges and limitations of AI?

According to a new Day Trading report, the excitement around the AI bubble points to signs of overvaluation reminiscent of the dot-com era. While some areas of AI are genuinely transformative, it’s not all boom or bust, but somewhere in the middle.

Dan Buckley, Chief Analyst at DayTrading.com, believes AI is a genuine technological boom, but it comes with pockets of overhype and speculation along the way. “We’re seeing record capital inflows, sky-high valuations, one-sided sentiment, and investing driven by FOMO before common sense. Yet we’re also seeing real-world use cases for AI and infrastructure investment at an industrial scale,” he said. “The best framing is generally that AI is a real boom containing localized bubbles, not a mania in the board.”

The question remains – is AI a bubble? A bubble refers to when the price of an asset, like a stock or share, and sometimes, even a whole industry, grows in financial value much higher than its actual worth. This typically happens due to overexcitement and investors “following the crowd,” rather than basing decisions on true factors like demand and profits.

Currently, a number of AI company prices, including Microsoft and Nvidia, are substantially higher than their actual earnings or sales. Normally, high stock prices are justified by high profits, but the valuations of newer AI companies are, at present, over-inflated as they assume large future profits that may never materialize. This is demonstrated by a significant $560 billion investment into AI by companies over the last two years, but the estimated incremental revenue from such companies is only £35 billion – a considerable $525 billion gap.

Society as a whole assumes AI will revolutionize just about everything, but Day Trading’s report discovered many companies are not generating enough earnings to warrant such excitement. Investors are pricing vast returns on young technologies in early adoption phases in a “hope” that returns will match their investments. Moreover, many companies are “AI washing,” a tactic to exaggerate their AI capabilities to market themselves as more valuable than perhaps traditional assessment.

Some established global players like Nvidia and Amazon finance their growth through robust cash flows, but many newer AI startups are relying heavily on venture capital or debt funding, thus making them highly vulnerable if funding conditions change. Current enthusiasm around AI can attract emergency funding in some cases, but this reliance on high-risk financing highlights the fragility present in some segments of the AI market.

Investor sentiment towards AI is very positive, but also bullish. Sceptical perspectives are rarely acknowledged, which may leave the AI market vulnerable to sudden corrections if confidence is lost. Historically, bubbles tend to coincide with rising volatility, but the S&P 500 has remained relatively calm so far, suggesting surface-level stability. However, this may reflect confidence among investors convinced of AI’s promise.

According to Day Trading, a surge in inexperienced investors jumping on the AI hype bandwagon may be inflating valuations and heightening the risk of sudden corrections. Much like behavior seen in the dot-com bubble, new buyers are following extant narratives, at present based on social media buzz and news headlines, instead of focusing on current earnings or real value.

Although interest rates are higher compared to pre-pandemic levels, major tech firms have enough liquidity to continue investing heavily in AI without taking too much risk. The ratio of fresh equity or uncertain borrowing remains relatively low.

Some AI companies, like CoreWeave and OpenAI, are aggressively hoarding resources, including AI chips and engineering talent, in anticipation of demand. This creates further financial risk if growth in sales were to slow. With no clear ROI or business models in place, capital is at the mercy of AI growth, or lack of it.

Day Trading’s report highlights a range of concerns, similar to the dot-com bubble of the late 1990s and early 2000s. For instance, AI is already being used at scale, delivering productivity gains, particularly in sectors like finance, logistics, and media, something that was not evident in the dot-com era.

Although AI companies claim to be creating real value right now, compared to infrastructure investments being made, only a few are enjoying profitable margins, like Microsoft and Nvidia. Substantial investments have been made for long-term growth, not short-term fast returns. Therefore, the true returns may yet materialize as AI’s full potential unfolds over time. Eric Schmidt, former CEO of Google described, “AI as infrastructure for a new industrial era, not just a passing tech fad.”

Dan Buckley does not think AI is just hype, but excessive optimism can be dangerous. “AI is real and valuable,” Buckley said. “But it’s when market sentiment outpaces real business results that I begin to worry about the gap becoming dangerous for investors.” 

Frequently Asked Questions (FAQS): 

Q: What is an AI bubble?

A: An AI bubble refers to the overvaluation of AI companies and stocks, where their financial value grows much higher than their actual worth due to excessive investor enthusiasm and speculation.

Q: What are some signs of overvaluation in the AI market?

A: Signs of overvaluation include sky-high stock prices, record capital inflows, one-sided sentiment, and investing driven by FOMO (Fear of Missing Out) rather than actual business results.

Q: How are newer AI startups different from established players like Nvidia and Amazon?

A: Newer AI startups often rely heavily on venture capital or debt funding, making them more vulnerable to changes in funding conditions, while established players like Nvidia and Amazon have robust cash flows to finance their growth.

Q: What is 'AI washing' and why is it a concern?

A: AI washing is a tactic where companies exaggerate their AI capabilities to appear more valuable. This can lead to overhyped market perceptions and inflated stock prices, increasing financial risks.

Q: What is the potential long-term impact of AI investments?

A: Substantial investments in AI are made for long-term growth and infrastructure development. While the immediate returns may not be significant, the full potential of AI is expected to unfold over time, delivering substantial value and productivity gains. 

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