Google\u2019s CEO, Sundar Pichai, has spoken<\/a> of \u201cirrationality\u201d in AI\u2019s growth, while others have said some projects are proving to be more complex and expensive than expected<\/a>. <\/p>\n Meanwhile, global stock markets have declined, with tech shares taking a particular hit, and the value of cryptocurrencies has dipped as investors appear increasingly nervous.<\/p>\n So how should we view the health of the AI sector? <\/p>\n Well, bubbles in technology are not new. There have been great rises and great falls in the dot-com world, and surges in popularity for certain tech platforms (during COVID for example) which have then flattened out. <\/p>\n Each of these technological shifts was real, but they became bubbles when excitement about their potential ran far ahead of companies\u2019 ability to turn popularity into lasting profits.<\/p>\n The surge in AI enthusiasm has a similar feel to it. Today\u2019s systems are genuinely impressive, and it\u2019s easy to imagine them generating significant economic value<\/a>. The bigger challenge comes with how much of that value companies can actually keep hold of. <\/p>\n Investors are assuming rapid and widespread AI adoption along with high-margin revenue. Yet the business models needed to deliver that outcome are still uncertain and often very expensive to operate.<\/p>\n This creates a familiar gap between what the technology could do in theory, and what firms can profitably deliver in practice. Previous booms show how quickly things wobble<\/a> when those ideas don\u2019t work out as planned. <\/p>\n AI may well reshape entire sectors, but if the dazzling potential doesn\u2019t translate quickly into steady, profitable demand, the excitement can slip away surprisingly fast.<\/p>\n Fit to burst?<\/p>\n Investment bubbles rarely deflate on their own. They are usually popped by outside forces, which often involve the US Federal Reserve (the US\u2019s central bank) making moves to slow the economy<\/a> by raising interest rates or limiting the supply of money, or a wider economic downturn suddenly draining confidence<\/a>. <\/p>\n For much of the 20th century, these were the classic triggers that ended long stretches of rising markets.<\/p>\n But financial markets today are larger, more complex, and less tightly tied to any single lever such as interest rates. The current AI boom has unfolded despite the US keeping rates at their highest level in decades, suggesting that external pressures alone may not be enough to halt it.<\/p>\n Instead, this cycle is more likely to end from within. A disappointment at one of the big AI players \u2013 such as weaker than expected earnings at Nvidia or Intel \u2013 could puncture the sense that growth is guaranteed. <\/p>\n Alternatively, a mismatch between chip supply and demand could lead to falling prices. Or investors\u2019 expectations could quickly shift if progress in training ever larger models begins to slow, or if new AI models offer only modest improvements.<\/p>\n Overall then, perhaps the most plausible end to this bubble is not a traditional external shock, but a realisation that the underlying economics are no longer keeping up with the hype, prompting a sharp revaluation across related stocks.<\/p>\n Artificial maturity<\/p>\n If the bubble did burst, the most visible shift would be a sharp correction in the valuations of chipmakers and the large cloud companies driving the current boom. <\/p>\n These firms have been priced as if AI demand will rise almost without limit. So any sign that the market is smaller or slower than expected would hit financial markets hard. <\/p>\n This kind of correction wouldn\u2019t mean AI disappears, but it would almost certainly push the industry into a more cautious, less speculative phase.<\/p>\n When the chips are down.![\"Computer](\"https:\/\/www.newsbeep.com\/au\/wp-content\/uploads\/2025\/11\/file-20251118-66-ja322k.jpg\")
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