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AI could boost labor productivity growth across the developed world by about 1.5 percentage points per year over a 10-year horizon, which could translate into a more than $4 trillion increase in annual global GDP.
Source: Goldman Sachs ·
Analyst note
This claim is a conditional macro translation: it depends on diffusion speed, complementarities, and regulation—not on whether chatbots impress consumers. Goldman’s incentives are analytical (sell research) but also subject to financial-industry enthusiasm about AI capex cycles.
A measured reading keeps three trackers: median firm adoption depth (not pilot counts), observable IT capital deepening with measurable output per hour, and sector heterogeneity (legal, software, customer ops) where automation is tractable. Labs like OpenAI and Google DeepMind influence the frontier, but macro outcomes hinge on deployment frictions.
Evidence timeline
Goldman published a global GDP and productivity translation of generative AI adoption scenarios, emphasizing a multi-year diffusion path rather than an instantaneous macro shock.
U.S. productivity prints showed episodic strength; attribution to AI remained contested as fiscal and interest-rate paths dominated headlines.
As of early 2026, mainstream macro forecasts remained split on whether AI-driven diffusion would show up clearly in TFP within a short window or only after capex and organizational redesign cycles.