- Updated: February 24, 2026
- 5 min read
AI’s Zero Impact on US Economic Growth: Goldman Sachs Analysis

Goldman Sachs’ latest analysis shows that artificial intelligence contributed essentially zero to U.S. economic growth in 2025.
Key Finding: AI’s Near‑Zero Impact on 2025 GDP
In a surprise turn, the Wall Street heavyweight concluded that despite billions of dollars poured into AI‑driven data centers, the net effect on the nation’s gross domestic product was virtually nil. The report challenges the prevailing narrative that AI spending is a new engine of growth and forces investors, tech leaders, and policymakers to rethink their strategies.
Read the original coverage on Gizmodo for the full story.
What the Goldman Sachs Report Actually Says
The analysis, authored by senior economist Jan Hatzius and AI analyst Joseph Briggs, examined quarterly GDP data, corporate capital expenditures, and import‑export balances. Their core conclusion:
“AI investment has had basically zero contribution to U.S. GDP growth in 2025. The narrative of a booming AI‑driven economy is largely a myth.”
Methodology and Data Sources
- National Income and Product Accounts (NIPA) for quarterly GDP.
- Custom survey of 6,000 senior executives across the U.S., Europe, and Australia.
- Custom import‑export tracking of AI‑related semiconductors and server hardware.
Core Numbers
| Metric | 2025 Value |
|---|---|
| Total AI‑related capex (U.S.) | $120 billion |
| AI‑related hardware imports | $85 billion |
| Measured contribution to GDP | ≈ 0 % |
Why AI Fell Short of Expectations
The report identifies two primary drivers behind the negligible GDP impact.
1. Imported Hardware Offsets Domestic Spending
U.S. firms are indeed spending heavily on AI, but the bulk of the required chips, GPUs, and high‑speed networking gear originates from Taiwan, South Korea, and China. In national accounts, these imports are counted as foreign production, which dilutes the domestic contribution.
As Hatzius put it, “A lot of the AI investment that we’re seeing in the U.S. adds to Taiwanese GDP, and it adds to Korean GDP but not really that much to U.S. GDP.”
2. Measurement Challenges and Productivity Lag
Current economic metrics struggle to capture the subtle, often indirect, productivity gains from AI. Unlike traditional capital equipment, AI’s value is embedded in software, data, and algorithmic improvements that are hard to quantify.
Furthermore, many enterprises are still in the pilot phase, meaning the technology has not yet scaled to a level that would meaningfully affect output per worker.
Executive Survey: AI’s Real‑World Productivity Impact
The Goldman Sachs team supplemented macro data with a fresh survey of 6,000 senior leaders. The findings paint a sobering picture:
- 70 % of respondents reported active AI usage in at least one business unit.
- Only 20 % observed a measurable boost in employee productivity.
- Nearly 80 % said AI had no discernible effect on hiring or workforce size.
These numbers contrast sharply with earlier optimism that AI would trigger a “productivity renaissance” within a single fiscal year.
What This Means for Tech‑Savvy Professionals and Investors
While the headline may seem discouraging, the nuanced insights offer actionable guidance for businesses looking to extract real value from AI.
Re‑evaluate Investment Strategies
Companies should shift focus from sheer spending on hardware to building robust AI ecosystems that prioritize data quality, model governance, and integration with existing workflows.
Leverage Integrated AI Platforms
Platforms that combine low‑code development, pre‑trained models, and seamless third‑party integrations can accelerate time‑to‑value. For example, the UBOS platform overview offers a unified environment where AI agents, data pipelines, and automation tools coexist.
Key capabilities include:
- AI marketing agents that personalize campaigns without extensive coding.
- The Workflow automation studio, enabling rapid orchestration of AI‑driven processes.
- Built‑in OpenAI ChatGPT integration for conversational interfaces.
Adopt Ready‑Made Templates for Faster ROI
UBOS’s templates for quick start let teams launch AI solutions in days rather than months. Notable examples include:
- AI SEO Analyzer – boosts organic traffic by automating keyword research.
- AI Article Copywriter – generates high‑quality content at scale.
- AI Video Generator – creates marketing videos without a production crew.
Integrate Voice and Multimodal AI
Emerging capabilities such as voice synthesis and multimodal reasoning can differentiate products. UBOS supports the ElevenLabs AI voice integration and the Chroma DB integration for vector search, enabling richer user experiences.
Consider the Global Supply Chain
Given the import‑heavy nature of AI hardware, firms should evaluate sourcing strategies, possibly exploring domestic semiconductor initiatives or partnering with manufacturers that offer on‑shoring options.
Looking Ahead: Turning Zero Into Growth
The Goldman Sachs findings are a wake‑up call, not a death knell. By aligning AI investments with measurable business outcomes, leveraging integrated platforms like UBOS homepage, and adopting proven templates, companies can convert today’s “zero” contribution into tomorrow’s competitive advantage.
Ready to accelerate your AI journey? Explore the UBOS partner program for co‑selling opportunities, or dive into the UBOS pricing plans to find a tier that matches your budget.
Stay informed, act strategically, and watch your AI initiatives finally move the needle on the bottom line.
Andrii Bidochko
CTO UBOS
Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.