Global AI Investment Is Forecast to Exceed $1 Trillion in 2026

The most commonly referenced estimate for investment in artificial intelligence (AI) is the projection for capital expenditure by US hyperscalers. These tech companies are forecast to spend about $800 billion this year, according to the consensus of analyst estimates. 

But these estimates have several drawbacks, according to Goldman Sachs Research. They do not include investment in AI by private companies or by companies outside the US—including firms in Asia. Not all capex by hyperscalers is necessarily related to AI. And major US tech companies operate globally, indicating some of their investment takes place outside the US. 

How much is being invested in AI around the world?

Goldman Sachs Research adjusted the widely cited measures of US hyperscaler capex to produce a more comprehensive estimate. That projection points to $1 trillion of AI-related investment around the globe in 2026, including $581 billion in the US, writes Joseph Briggs, who co-leads the Global Economics team, in a report.  

These augmented estimates indicate that the commonly cited forecast for hyperscaler capex of $794 billion likely understates the total amount of global AI capex by around $200 billion. At the same time, the $794 billion figure likely overstates the amount of US investment in AI by $200 billion. 

How Goldman Sachs Research estimates global AI investment

Goldman Sachs Research augmented the frequently cited measurement of hyperscaler capex in several key ways: 

• Our economists included capex projections for public companies other than hyperscalers in the US that are included in Goldman Sachs’ baskets of AI-related stocks. They also collected media reports of capex for key private companies that are pivotal in the AI ecosystem. 
• Goldman Sachs Research added capex projections for AI-exposed companies outside the US. 
• Our economists adjusted total capex spending by subtracting off 2022 capex levels for US hyperscalers. (This adjustment is motivated by our equity analysts’ views that nearly all incremental capex since 2022 has been allocated toward AI projects.) They similarly attribute all capex to AI for the private companies that are included. For less directly exposed and non-US companies, Goldman Sachs Research also assumes capex in excess of 2022 levels is AI related.  
• Whenever possible, Goldman Sachs Research excludes financial leases that could otherwise be double-counted as hardware capex by other companies. 
• To estimate where the investment takes place, Goldman Sachs Research leveraged data on the reported locations of announced investment projects (mainly from US hyperscalers). Our economists also assume that AI investment for most other non-hyperscalers (both private and global companies) follows a similar pattern, but that AI investment by major Chinese and Korean AI-exposed companies occurs outside of the US. 

Briggs notes that these estimates rely on some assumptions that are hard to verify. There is also some risk of double-counting capex for AI for some companies that do not report property, plant, and equipment investment separately from financial leases in their capex statements. Therefore, Goldman Sachs Research cross-checked its estimates against two other approaches. 

For a proxy for overall AI investment, our economists looked at gross profit realizations and forecast revisions relative to 2022 projections for public companies exposed to the AI buildout. They also used official government data to trace out the increase in nominal AI investment, and they used global trade data and the observed relationship between US imports and total AI investment to impute total investment in other economies.  

The two cross-checks imply a pace of investment remarkably similar to Goldman Sachs Research’s preferred measure of augmented hyperscaler capex. Each of the cross-checks suggests that AI investment will total around $1 trillion globally and just under $600 billion in the US in 2026.  

While the cumulative investment totals since 2022 implied by the different methodologies to prior years diverge a bit, on average they suggest that cumulative investment in AI will total $1.8 trillion by the end of this year, Briggs writes. 

What is the outlook for AI investment?

“The AI capex growth outlook, including how high AI investment ultimately rises as a share of GDP and when capex growth slows, is a key source of uncertainty for macro markets right now,” Briggs writes.  

Goldman Sachs Research extrapolated its preferred estimates for AI investment to forecast total AI investment as a share of US GDP through 2028. Those estimates imply that AI capex will rise from 1.8% of GDP in the US (with global AI investment totaling 0.9% of global GDP) in 2026 to 2.5% of GDP in the US (1.3% globally) in 2027, with a further increase to 2.8% (1.4% globally) in 2028. 

“These levels are consistent with the 2%-5% of GDP peak investment impulses observed in prior general-purpose technology buildouts,” Briggs writes. “And while our US portfolio strategy team has flagged that consensus capex projections for 2027 are likely too conservative, even significant upward revisions would leave the level of AI investment as a share of GDP comfortably within the historical range observed in prior technology cycles.” 

To estimate when the growth in AI-related capex will slow, Goldman Sachs Research says a “dashboard approach is most appropriate.” Our economists compiled a broad set of leading indicators—including semiconductor manufacturing equipment imports in Taiwan and South Korea, relevant Purchasing Managers’ Index (PMI) indicators and components, import prices, and memory purchase and Graphics Processing Unit (GPU) rental prices—to check whether a slowdown is imminent. Our economists find that their selected indicators provide leading information about US AI capex growth.  

“The good news for the capex outlook is that all leading indicators rank near the top end of their range since 2022,” Briggs writes. “This pattern suggests a robust near-term growth outlook.” 

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