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Scanning the headlines, it can be easy to get the impression that every investor, banker, and financial analyst is enamored with AI. Yet this simplified view obscures a more complicated story: the US economy isn\u2019t where tech companies say it is.<\/p>\n
By and large, businesses have gone bonkers over automation, lavishing $410 billion<\/a> on AI in 2025 alone. To them, it\u2019s a productivity miracle. AI should obviously make everybody work faster, reducing the need for human labor as it takes less staff to do more \u2014\u00a0saving companies gobs of cash in the long run.<\/p>\n At least, that\u2019s the narrative in the corporate world. In banking, however, Goldman Sachs is spinning another yarn. After months of carefully-worded warnings about the dangers of over-investing on AI, Goldman has now dramatically escalated its rhetoric: the bank\u2019s analysts now claim that AI has had zero impact<\/a> on US economic growth over 2025.<\/p>\n The disconnect between AI investment and growth comes down to two structural issues. The first is geographic<\/a>: when US companies buy chips from Taiwan, for example, that money boosts Taiwan\u2019s economy, not the US. Second is productivity<\/a>. AI might make some workers faster, sure, but that speed doesn\u2019t automatically make supply chains more efficient \u2014 so far, those productivity gains are largely trapped inside company walls.<\/p>\n This pushback on AI\u2019s economic impact marks a sharp break from even the most cynical analyses of 2025<\/a>, in which even doomers credited the technology with single-handedly keeping US GDP growth afloat. Though the market more broadly has yet to see things Goldman\u2019s way \u2014 investors are projected to spend $660 billion on AI across 2026 \u2014 a growing number of analysts are starting to cry foul.<\/p>\n Dario Perkins, head of macroeconomics at consulting firm TS Lombard, agrees that AI\u2019s effects on productivity are nonexistent, even as massive layoffs<\/a> have the workforce reeling. He was recently quoted in the Financial Times<\/a>, arguing that \u201cthere is no evidence that AI deployment is either boosting productivity or damaging US employment.\u201d<\/p>\n \u201cWhile US productivity has been strong and hiring weak, our analysis finds that cyclical forces \u2014 not automation \u2014 are to blame,\u201d Perkins concluded.<\/p>\n Meanwhile, former bank regulator at the New York Fed Brian Peters recently wrote<\/a> that, while AI\u2019s \u201ccapabilities are extraordinary\u201d and the \u201ccapital deployment is unprecedented,\u201d the \u201cnear-term economic payoff is, at best, debatable.\u201d<\/p>\n At the National Bureau of Economic Research, economists studying the effects of AI on productivity recently published a working paper<\/a> identifying a \u201cproductivity paradox,\u201d where \u201cperceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations.\u201d<\/p>\n The implications of all this are stark. An investment boom measured in the hundreds of billions has, by Goldman\u2019s accounting, generated essentially no measurable economic return for the US. The question facing us now in 2026 is whether $660 billion more of the same will produce anything other than an even bigger AI bubble.<\/p>\n