Goldman Sachs Survey: AI Investment Growth Remains Strong, with AI Adoption Rate Among Large U.S. Companies Reaching 15%
Goldman Sachs' survey shows that the adoption rate of AI by U.S. companies in the second quarter has significantly jumped from 7.4% in the fourth quarter of last year to 9.2%, with large enterprises having more than 250 employees reaching an adoption rate of 14.9%. The most important signal is that the revenue expectations for the semiconductor industry are projected to grow by 36% from current levels by the end of 2026, and the revenue forecast for 2025 has been raised
While Wall Street is still debating the AI bubble, the latest data on AI adoption rates among American companies and revenue expectations for semiconductor companies seem to reveal the true face of this AI revolution.
On June 6th, according to news from the Chasing Wind Trading Desk, Goldman Sachs' AI adoption tracking report for Q2 2025 shows that the AI adoption rate among American companies has significantly jumped from 7.4% in Q4 last year to 9.2%, with the adoption rate for large enterprises with more than 250 employees reaching as high as 14.9%.
Goldman Sachs chief analysts Jan Hatzius, Joseph Briggs, and others stated in the report that the most important signal for the market is that semiconductor industry revenue expectations are projected to grow by 36% by the end of 2026 compared to current levels, and analysts have raised their revenue forecasts for the semiconductor industry and AI hardware companies for 2025.
The analysis pointed out that this expectation adjustment reflects the sustainability of the AI investment boom.
AI Investment Growth Remains Strong
Semiconductor companies continue to be the biggest beneficiaries of the AI investment wave.
Goldman Sachs stated in the report that since the release of ChatGPT, analysts have raised the semiconductor industry's revenue forecast for the end of 2025 by $200 billion and increased the forecasts for other AI hardware companies by $105 billion.
In addition to semiconductors, revenue forecasts for cloud service providers and utility companies have also been raised by analysts.
Investment in AI-related hardware and software in the U.S. accelerated in the first quarter; however, Goldman Sachs believes that due to the methodology issues of the U.S. Census Bureau treating semiconductors and cloud services as intermediate inputs, this growth may be underestimated.
Goldman Sachs noted that this statistical blind spot reveals the limitations of traditional economic statistical frameworks in capturing the true scale of AI investments, which also explains why the AI boom is not as evident in macroeconomic data as expected.
Acceleration of Corporate AI Adoption Rates
Data at the corporate level is even more striking.
The report pointed out that significant progress has been made in corporate AI adoption by Q2 2025, with 9.2% of American companies currently using AI to produce goods or services, a substantial increase from 7.4% in Q4.
In terms of industry distribution, education, information, finance, and professional services companies reported the largest increases in adoption rates, growing by more than 3 percentage points compared to the previous quarter.
Broadcasting and telecommunications companies expect the largest increase in AI adoption rates in the next six months. Goldman Sachs observed that sub-industries where work tasks are more susceptible to AI automation have higher adoption rates, and this correlation remains strong.
From the perspective of company size, large enterprises with more than 250 employees continue to maintain the highest adoption rate at 14.9%, while medium-sized enterprises with 100-249 employees are expected to see the largest increase in adoption rates over the next six months, reaching an increase of 4.7 percentage points to 14.6%. Medium-sized enterprises with 150-249 employees also saw an acceleration in adoption rates.
Despite the rapid growth in AI adoption rates, the impact of AI on the labor market remains limited, with most labor market indicators showing no significant signs of impact.
The report states that AI-related job vacancies currently account for 24% of all IT job vacancies and 1.5% of all job postings In addition, Goldman Sachs pointed out that in the limited areas where generative AI has been deployed, there has been a significant increase in labor productivity. Data shows that academic research indicates an average productivity increase of 23%, while corporate examples show an efficiency improvement of about 29%.
Goldman Sachs believes that the limited but significant productivity paradox may suggest that the true disruptive impact of AI has not yet been fully unleashed
