Goldman Sachs' Joseph Briggs: Gen AI could lift U.S. labor productivity 15% in 10 years

Joseph Briggs, a senior global economist at Goldman Sachs, recently shared insights on the macroeconomic implications of generative AI, projecting a significant uplift in U.S. labor productivity. Speaking with CNBC's 'Squawk on the Street', Briggs elaborated on the potential of AI to transform the economy.

Briggs spoke with CNBC's 'Squawk on the Street' about macro outlooks, how AI investment could show returns, and the broader impact of artificial intelligence. His analysis suggests that while current AI adoption is nascent, the long-term economic benefits could be substantial.

A key takeaway from Briggs' discussion is the potential for generative AI to significantly enhance labor productivity. He stated, "Gen AI could lift U.S. labor productivity 15% in 10 years." This projection is based on an assessment of how AI technologies can automate tasks, augment human capabilities, and streamline workflows across various sectors.

The scale of investment in AI infrastructure is already considerable, with Big Tech companies leading the charge. Data presented indicated substantial quarterly spending on AI-related capital expenditures. However, Briggs cautioned against viewing this spending in isolation, emphasizing the need to scale these figures against GDP to understand their true economic significance. When discussing the current state of AI adoption, Briggs noted, "Only -10% of U.S. firms currently use AI in production, room to grow." This statistic underscores the significant untapped potential for AI to drive productivity gains across the economy.

Furthermore, early case studies provide empirical evidence supporting the optimistic outlook. Briggs highlighted that "Early enterprise case studies show 25-30% productivity boosts." These findings suggest that companies actively integrating AI are already realizing tangible improvements in efficiency and output. This points to a clear path for AI to deliver value beyond mere technological advancement, translating directly into economic growth.

Related Reading

• AI's Relentless March: Efficiency, Autonomy, and Economic Reshaping
• XPO's AI-Driven Efficiency in a Soft Freight Market
• MIXI's Enterprise AI Adoption: A Blueprint for Accelerated Efficiency

The discussion also touched upon the historical parallels of technological adoption, drawing comparisons to the internet era and the rollout of electric vehicles. Briggs suggested that the current AI investment cycle might mirror these past transformative periods, indicating a potential for broad-based economic expansion driven by AI adoption. He elaborated, "We are seeing signs of labor market impacts and some of the sectors that are most exposed to the build out of AI... you've seen labor growth slow, particularly in the tech sector." This suggests that the initial stages of AI integration may involve shifts in employment patterns.

The core insight from Briggs' analysis is that the current wave of AI investment, particularly in generative AI, is not merely a speculative bubble but a foundational shift with the potential to reshape the economic landscape. The projected productivity gains, supported by early empirical evidence, indicate a robust return on investment for companies embracing these technologies. The relatively low current adoption rate also suggests a significant runway for future growth and economic impact.