{"id":84942,"date":"2025-08-21T12:32:09","date_gmt":"2025-08-21T12:32:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/84942\/"},"modified":"2025-08-21T12:32:09","modified_gmt":"2025-08-21T12:32:09","slug":"ai-is-failing-at-an-overwhelming-majority-of-companies-using-it-mit-study-finds","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/84942\/","title":{"rendered":"AI Is Failing at an Overwhelming Majority of Companies Using It, MIT Study Finds"},"content":{"rendered":"

With AI software increasingly hogging the enterprise spotlight, companies and investors are spending like never before. In the first half of 2025, AI startups<\/a> raised over $44 billion, more than all of 2024 combined. By the end of this year, a Goldman Sachs analysis<\/a> estimates that total investments in AI will soar to\u00a0 almost\u00a0$200 billion.<\/p>\n

But all that money is, to put it gently, a reckless gamble. In the US at least, investors have essentially bet the farm on the idea that AI will soon lead to gains in labor productivity<\/a> \u2014 the amount of goods and services workers are able to produce in a given time \u2014 that have never been seen in the history of humankind<\/a>.<\/p>\n

Despite the hype and bluster, that isn’t happening. A new report by researchers at MIT, first covered by Fortune<\/a>, found that a staggering 95 percent of attempts to incorporate generative AI into business\u00a0so far are failing.<\/p>\n

According to the report, titled “The GenAI Divide: State of AI in Business 2025,” the MIT researchers found that only around 5 percent of businesses succeed at “rapid revenue acceleration,” with the vast majority falling flat.<\/p>\n

Looking beyond the AI marketing hype<\/a>, it’s not hard to see why this is. Previous research into this kind of AI, which is marketed as a sort of autonomous assistant<\/a> for white collar workers, found that the tech falls way short of the mark.<\/p>\n

As of July, the best AI products successfully completed just 30 percent<\/a> of the real-world office tasks assigned to them, with most doing significantly worse.<\/p>\n

Given that AI was previously expected<\/a> to contribute over $6 trillion to the global economy by 2030, the productivity gains from here on out would have to be nearly exponential<\/a> to live up to expectations.<\/p>\n

For example, a recent analysis by <\/a>MoneyWeek<\/a> argued that, with so much money riding on AI, anything less than a complete upheaval of the world as we know it will look like a failure. A typical financial analysis indicates that the top seven big tech companies should be seeing an extra $600 billion in yearly revenue \u2014 a number so large it’s nearly meaningless. (As of this year, for perspective, they’re projected to nab around $35 billion annually.)<\/p>\n

Every year AI fails to return these ever-higher numbers, the need for labor productivity to increase goes up \u2014 at least if Wall Street hopes to justify its spending spree \u2014 effectively kicking the half-a-trillion-dollar can down the road<\/a>.<\/p>\n

Without a major breakthrough in the immediate future, it’s looking more and more like a matter of “when” rather than “if” the AI bubble will pop<\/a> \u2014\u00a0with potentially disastrous implications for the broader economy<\/a>.<\/p>\n

More on AI: Companies That Replaced Humans With AI Are Realizing Their Mistake<\/a><\/p>\n

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