- Goldman Sachs says $410 billion invested in AI during 2025 generated no measurable impact on US GDP.
- Optimistic analyses attributing up to 92% of economic growth to AI have been debunked by more rigorous data.
- Difficulty separating AI spending from general technology investments distorts economic measurements.
- Economists warn we're in an early phase similar to internet development, where returns take longer than expected.
Artificial intelligence captured headlines with trillion-dollar investment figures in 2025, but its actual contribution to US economic growth was negligible according to Goldman Sachs' latest analysis. Chief economist Jan Hatzius stated that AI's impact on GDP growth was "basically zero," challenging optimistic forecasts that predicted immediate economic transformation.
This revelation challenges narratives about immediate economic transformation through AI and suggests investment returns will take longer, affecting business decisions and public policy.
The Investment-Return Disconnect
Technology companies poured approximately $410 billion into AI development during 2025, with plans to increase that figure to $650 billion in 2026. This capital flood was justified by promises of radical productivity gains, process automation, and labor cost reductions. However, macroeconomic data tells a different story.
Hatzius explains there's a fundamental confusion between investment and economic return. "Just because a lot of money is spent on something doesn't mean it generates immediate economic value," the economist noted. This perspective starkly contrasts with earlier analyses that attributed up to 92% of US economic growth to AI during certain 2025 periods.
$410 billion invested in AI during 2025 generated no measurable impact on US economic growth.
The Economic Measurement Debate
Economist Hanna Rubinton from the Federal Reserve Bank of St. Louis had estimated that AI spending contributed 39% to economic growth during the first nine months of 2025. However, her own analysis acknowledged methodological limitations, including difficulty separating specific AI spending from general software and hardware investments.
JP Morgan and Morgan Stanley have aligned with Goldman Sachs' position, arguing that real economic contribution figures are far more modest than headlines suggest. The fundamental problem lies in how to measure the actual impact of technologies in early implementation phases, where development costs significantly outweigh immediate economic benefits.
The Bifurcated Economy
Reuters documented in November 2025 what it called a "bifurcated economy" created by the AI investment boom. While GDP showed 4% growth, layoffs increased across several sectors, possibly accelerated by automation processes. This disconnect between macroeconomic indicators and labor reality complicates assessing AI's true impact.
Massive investment in AI infrastructure, particularly chips and data centers, distorts traditional economic metrics. Hardware spending appears as economic growth in statistics but doesn't necessarily translate to increased productivity or sustainable value creation.
“There's much misinformation about AI investment's impact on US GDP. The actual contribution in 2025 was basically zero.”
Future Implications
Goldman Sachs' skepticism doesn't mean AI lacks transformative potential, but rather that its economic impact will take longer than anticipated. Hatzius suggests we're in a phase similar to the early internet years, where initial investments far exceeded immediate returns but laid foundations for later transformations.
For companies seeking to implement AI solutions, tools like GLM offer advanced capabilities without requiring the massive investments of big tech firms. This democratization could accelerate real, measurable technology adoption.
“Markets are always looking at the future, not the present.”
— Xataka
The true test will come when AI implementations mature and begin generating measurable efficiencies in business processes. Until then, the disconnect between investment and economic results will likely persist, challenging the most optimistic narratives about immediate economic transformation.