{"id":285308,"date":"2025-11-15T19:40:11","date_gmt":"2025-11-15T19:40:11","guid":{"rendered":"https:\/\/www.newsbeep.com\/ca\/285308\/"},"modified":"2025-11-15T19:40:11","modified_gmt":"2025-11-15T19:40:11","slug":"the-ai-bubble-greater-fool-authored-by-garth-turner-the-troubled-future-of-real-estate","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ca\/285308\/","title":{"rendered":"The AI bubble \u2014 Greater Fool \u2013 Authored by Garth Turner \u2013 The Troubled Future of Real Estate"},"content":{"rendered":"

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\nSource: Yurbed.com
\n\"RYAN\"\u00a0 \u00a0<\/a>By Guest Blogger Ryan Lewenza
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From CNBC headlines to client conversations, one topic dominates right now: Is today\u2019s AI boom echoing the dotcom bubble of 2000 \u2013 and are we headed for a similar drop? With the spotlight squarely on this important issue, I\u2019m tackling it headon today, offering my perspective on whether the current surge in AI is just hype or the next big thing.<\/p>\n

Let\u2019s first separate the extraordinary technological advancement of AI from the lens of investing. From a purely technological perspective, AI stands as one of the most transformative innovations of our lives \u2013 on par with the printing press, electricity, the steam engine, and the internet.<\/p>\n

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Source: Elon Musk\u2019s xAI datacentre in Memphis<\/p>\n

I use AI chatbots like ChatGPT, Copilot, and Grok with increasing frequency, and each week I discover new and productive applications. Though still in its relative infancy, AI is evolving at such a rapid pace that we can barely envision what the technology and advancements will look like in 3, 5, or 10 years.<\/p>\n

The potential is staggering: AI will reshape the workplace, revolutionize how we learn and consume information, accelerate scientific breakthroughs, and perhaps even play a role in humanity\u2019s journey to becoming multiplanetary \u2013 living on Mars or beyond.<\/p>\n

Today\u2019s focus is not on the incredible technology, but rather the investing world around AI.
Let\u2019s begin with the positives for AI.<\/p>\n

First, like the introduction of the internet which led to the creation of new products like the iPhone, new services like Uber, and new apps like my Peloton app, AI will lead to whole new products, services and apps being created. This will generate billions in new revenue streams and profits for companies.<\/p>\n

Second, AI promises sweeping productivity gains by automating tasks. It will streamline administrative work, enhance customer service, and transform manufacturing through robotics. Since productivity is a key driver of long-term economic growth, these efficiencies could translate into higher GDP growth.<\/p>\n

Third, across America and around the world, there are hundreds of massive data centres being built as the big tech companies like Meta, Amazon and Google, race to build out their AI networks. This includes building the physical structures, computers to run the AI programs, graphic processing units (GPUs) from Nvidia, network switches and massive amounts of power to run the data centres.<\/p>\n

This year alone, the major tech players \u2013 known as hyperscalers \u2013 are projected to spend US$500 billion on building data centres, a figure that\u2019s expected to keep climbing. This capital expenditure is essential for scaling AI infrastructure, and so far, there\u2019s little indication of a slowdown. However, when this spending eventually tapers off, it could expose vulnerabilities in AI-related stocks, potentially triggering a broader market reaction.<\/p>\n

Importantly, today\u2019s AI boom differs significantly from the dotcom bubble of the early 2000s. Back then, many unprofitable startups soared to billion-dollar valuations despite having minimal revenues and no earnings. In contrast, the current AI landscape is dominated by highly profitable tech giants like Amazon and Microsoft. This distinction matters: even if enthusiasm around AI cools, the financial strength of these companies suggests we\u2019re unlikely to see a collapse on the scale of the early 2000s \u2013 when the Nasdaq plunged more than 70%.<\/p>\n

Big tech \u2018hyperscalers\u2019 investing billions in AI<\/p>\n

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Source: Bloomberg, Raymond James Strategy<\/p>\n

Now let\u2019s turn to the concerns around AI \u2013 some of which have been keeping me up at night.
First, there\u2019s the sheer volume of hype and capital flooding into the space. Back in 2000, the excitement centered around the internet and laying fiber optic cables across the globe. Today, the spotlight is on AI, with billions being poured into building data centres. Having witnessed this kind of exuberance before, my \u2018Spidey sense\u2019 is tingling.<\/p>\n

Second, valuations are climbing fast and getting up there. The massive gains posted by leading AI companies have pushed valuations to elevated levels. For example, the S&P 500 Information Technology sector currently trades at a forward P\/E ratio of 38x, which is above its long-term average of 25x. Importantly, while this is still well below the peak levels seen during the 2000 tech bubble, it\u2019s a reminder that today\u2019s AI surge, while different in many ways, is not immune to the risks of overvaluation.<\/p>\n

S&P 500 information technology sector P\/E ratios<\/p>\n

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Source: Bloomberg, Turner Investments<\/p>\n

Third, the central question behind this investment frenzy is whether it will ultimately generate future revenues and profits. The critical metric here is return on investment (ROI). Take Meta, for example: the company is projected to spend an astonishing US$60 billion on AI initiatives this year alone. The real issue is whether such massive expenditures will translate into meaningful financial returns.<\/p>\n

Interestingly, a recent report from MIT researchers revealed a sobering insight: 94% of AI investments to date have not resulted in increased revenues or profits. This raises a fundamental concern \u2013 what if AI fails to deliver the transformative business models and revenue streams many are banking on? Will this historic wave of spending prove to be a miscalculation?<\/p>\n

Next, consider the growing circularity within the AI ecosystem. Circularity refers to the intricate web of interdependencies among AI companies. For instance, Nvidia has invested in ChatGPT, which in turn uses those funds to secure long-term contracts with Oracle. This interconnectedness means that a slowdown in spending by one player could ripple across the entire sector, impacting multiple companies simultaneously. The infographic below illustrates these complex relationships.<\/p>\n

AI is poised to reshape our world. While it offers groundbreaking capabilities, it also poses risks such as potential job displacement. We\u2019re monitoring AI and tech stocks closely, as concerns are mounting. However, as long as major tech firms continue pouring resources into AI and expanding their data centre infrastructure, this rally may still have momentum.<\/p>\n

Increasing \u2018circularity\u2019 of the AI ecosystem<\/p>\n

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Source: Morgan Stanley
\nRyan Lewenza, CFA, CMT is a Partner and Portfolio Manager with\u00a0Turner Investments<\/a>, and a Senior Investment Advisor, Private Client Group, of Raymond James Ltd.<\/p>\n

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