{"id":171714,"date":"2025-09-22T23:21:31","date_gmt":"2025-09-22T23:21:31","guid":{"rendered":"https:\/\/teknomers.com\/en\/big-tech-companies-are-currently-allocating-up-to-70-of-their-ebitda-to-ai-similar-to-the-figures-before-the-outbreak-of-the-pandemic\/"},"modified":"2025-09-22T23:21:32","modified_gmt":"2025-09-22T23:21:32","slug":"big-tech-companies-are-currently-allocating-up-to-70-of-their-ebitda-to-ai-similar-to-the-figures-before-the-outbreak-of-the-pandemic","status":"publish","type":"post","link":"https:\/\/teknomers.com\/en\/big-tech-companies-are-currently-allocating-up-to-70-of-their-ebitda-to-ai-similar-to-the-figures-before-the-outbreak-of-the-pandemic\/","title":{"rendered":"Big Tech companies are currently allocating up to 70% of their EBITDA to AI, similar to the figures before the outbreak of the pandemic."},"content":{"rendered":"\n

The race for \u00a0artificial intelligence\u00a0 dominance among major tech companies has escalated into a frantic competition, marked by enormous investments in infrastructure. This drive incorporates the construction of \u00a0data centers\u00a0, acquisition of chips, and expansion of computational capabilities. According to experts, these spending patterns mirror the exorbitant investments seen during previous market bubbles.<\/p>\n

Echoes of the Dot-Com Bubble<\/strong>. Tech giants are currently channeling between \u00a050% and 70%\u00a0 of their EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) into capital expenditures, mostly related to AI and cloud infrastructure. This observation comes from an analysis by GQG Partners<\/a>. Historically, such levels of investment are reminiscent of AT&T’s behavior during the dot-com bubble, which allocated \u00a072%\u00a0 of its earnings to fixed asset investments, similar to what Exxon did during the energy bubble in 2014<\/a> at \u00a065%\u00a0.<\/p>\n

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Percentage of operational benefit that Big Tech are spending against the level of AT&T and Exxon before bubbles. Image: GQG Partners<\/span>\n <\/div>\n<\/p><\/div>\n<\/div>\n

Concerns Unfolding<\/strong>. GQG Partners and analysts like Tobias Carlisle<\/a>, founder of Acquirer’s Funds, warn that such high spending is often a red flag. The concerns center around the risk of \u00a0obsolete assets\u00a0, delayed returns, and significant ongoing expenditures without guaranteed immediate benefits. The graph detailing the percentages of operational benefits spurred into fixed assets (CAPEX) by companies like \u00a0Microsoft\u00a0, \u00a0Amazon\u00a0, \u00a0Alphabet\u00a0, \u00a0Meta\u00a0, and \u00a0Oracle\u00a0 elucidates this trend.<\/p>\n

Investment Details<\/strong>. Current market dynamics reveal a strong investor appetite, compelling companies to adjust their forecasts dramatically. \u00a0Alphabet\u00a0, for instance, plans to spend over \u00a0$85 billion\u00a0 this year, primarily fortifying its cloud services. \u00a0Meta\u00a0 is preparing to invest between \u00a0$66 billion and $72 billion\u00a0 in 2025, projecting a massive investment of \u00a0$600 billion\u00a0 by 2028. Likewise, \u00a0Microsoft\u00a0 has earmarked tens of billions for new facilities aimed at expediting AI model training. The \u00a0Financial Times\u00a0 anticipates the annual capital expenditure of major tech companies to surpass \u00a0$300 billion\u00a0, marking an unprecedented figure in the industry.<\/p>\n

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\n \"AI\n <\/div>\n<\/p><\/div>\n<\/div>\n

However, this level of investment raises eyebrows among analysts. \u00a0Goldman Sachs\u00a0 recently sounded the alarm regarding \u00a0hyperscalers\u00a0 like AWS, Microsoft Azure, and Google Cloud, pointing out that they have collectively committed hundreds of billions in Capex and R&D. For these firms to justify such investments, they must generate significantly \u00a0higher revenues\u00a0 in the upcoming years. Conversely, \u00a0Bank of America\u00a0 cautions that the depreciation and amortization costs of this infrastructure could escalate even faster than the income generated, risking their operational margins.<\/p>\n

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Analysts at \u00a0Morningstar\u00a0 caution that the \u00a0semiconductor industry\u00a0, which serves as a pivotal element in this race, is prone to cyclical booms and busts. They predict a potential cooling off from the current investment enthusiasm into \u00a02025-2026\u00a0. Notably, Sam Altman, CEO of OpenAI, has publicly acknowledged a “bubble” surrounding artificial intelligence, yet he maintains that the underlying technology holds immense \u00a0long-term value\u00a0.<\/p>\n

Potential Risks Ahead<\/strong>. Investing heavily in infrastructure does not automatically translate to future income that compensates such high expenses. While optimistic investor sentiment may sustain current capital raises, doubt and uncertainty could upend this trend. The GQG Partners analysis also highlights potential “hidden” costs such as accelerated depreciation, technological obsolescence, and the maintenance and energy consumption of data centers\u2014factors that may erode profit margins faster than anticipated.<\/p>\n

The tech industry is embarking on a dramatic phase of investment in AI and infrastructure\u2014marked by both exhilaration and trepidation. As companies forge ahead, balancing capital expenditures against market realities will be paramount in determining the sustainability and profitability of their ambitious ventures. Continuous monitoring of these developments will be essential for investors and stakeholders alike, as they navigate the complexities of a rapidly evolving technological landscape.<\/p>\n


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General News – 2<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The race for \u00a0artificial intelligence\u00a0 dominance among major tech companies has escalated into a frantic competition, marked by enormous investments in infrastructure. This drive incorporates the construction of \u00a0data centers\u00a0, acquisition of chips, and expansion of computational capabilities. According to experts, these spending patterns mirror the exorbitant investments seen during previous market bubbles. Echoes of […]<\/p>\n","protected":false},"author":1,"featured_media":171715,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36399],"tags":[36873,363,1723,37664,4990,2827,754,3464,18527],"class_list":["post-171714","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-allocating","tag-big","tag-companies","tag-ebitda","tag-figures","tag-outbreak","tag-pandemic","tag-similar","tag-tech"],"_links":{"self":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/171714","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/comments?post=171714"}],"version-history":[{"count":0,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/171714\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media\/171715"}],"wp:attachment":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media?parent=171714"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/categories?post=171714"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/tags?post=171714"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}