Tech, AI to speed up US productivity, GDP growth: economists

Goldman Sachs economists project US productivity growth to accelerate to an average of 1.7% through 2029 and 1.9% in the early 2030s, up from 1.2% pre-pandemic, driven by increasing AI adoption and investment. This is expected to boost potential GDP growth to 2.1% (2025-2029) and 2.3% (early 2030s), with AI contributing approximately 0.4% to GDP in the near term and 1.5% cumulatively long-term. While temporary frictional unemployment is anticipated, the outlook presents both upside risks from faster AI adoption and downside risks from underperforming AI capital expenditure or slower technological progress.

Analysis

A Goldman Sachs research note projects a significant structural acceleration in US productivity and potential GDP growth, driven primarily by technological innovation and the increasing adoption of artificial intelligence. Economists forecast that labor productivity growth, which averaged 1.2% pre-pandemic, will rise to an average of 1.7% through 2029 and 1.9% in the early 2030s. This productivity enhancement is expected to lift potential GDP growth to 2.1% between 2025 and 2029, and further to 2.3% in the early 2030s. The report specifically quantifies AI's contribution, estimating it will boost GDP by approximately 0.4% in the near term and a cumulative 1.5% in the long run. While acknowledging that it may be premature to fully attribute recent gains to AI, the note anticipates a temporary rise in frictional unemployment as a consequence of AI adoption, which would paradoxically increase capital per worker and further boost productivity. The outlook is presented with balanced risks: upside potential from faster-than-expected AI adoption versus downside risks from underperforming AI capital expenditure, slowing population growth, or a deceleration in technological progress.

Key Decisions for Investors

• Investors should consider increasing strategic allocation to US equities, particularly in technology and industrial sectors poised to benefit directly from increased AI-related capital expenditure and efficiency gains.
• It is crucial to monitor macroeconomic indicators for validation of this thesis, specifically tracking corporate capex in AI and related technologies, alongside labor market data for any signs of a more disruptive-than-expected rise in unemployment.
• Given the forecast's long-term nature, with significant benefits projected into the 2030s, portfolio positioning in AI beneficiaries should be viewed with a long-term horizon, recognizing that the full 1.5% cumulative GDP impact will materialize over an extended period.
• Re-evaluate long-term interest rate and inflation expectations, as a sustained, non-inflationary growth environment driven by productivity could lead to a more favorable macro backdrop than currently priced by markets.