Banking giant Goldman Sachs says companies are spending a lot more on AI than anticipated, way faster than their budgets were designed to handle.
In a new post on X, Atreides Management CIO Gavin Baker shares an excerpt from a Goldman Sachs report, which notes that companies are now spending nearly a tenth of their headcount budget on AI inference.
“Companies are overrunning their initial budgets for inference by orders of magnitude. We heard one industry datapoint on inference costs in engineering now approaching about 10% of headcount cost, but could be on track to be on par with headcount costs in the next several quarters based on current trajectories.”
AI inference is the process of using a trained machine learning model to make real-world predictions, decisions or generative outputs based on new and unseen data. Goldman Sachs suggests that AI inference costs are rapidly becoming one of the largest operating expenses a company carries, and could be comparable in scale to its entire salary bill.
Goldman’s data comes as the Big Four accounting firm KPMG says firms in the US and across the world are looking to spend tens of millions of dollars in AI this year.
In its Global AI Pulse: Q1 2026, KPMG drew insights from more than 2,100 senior leaders and found that global organizations plan to spend a weighted average of $186 million on AI over the next 12 months, with US companies budgeting $178 million, Asia-Pacific organizations leading at $245 million, and EMEA organizations committing $157 million.
Taken together, the two reports tell the same story from opposite ends: companies are spending more on AI than they had planned and plan to spend even more.
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