AI Productivity's $4 Trillion Question: Hype, Hope, And Hard Data [Forbes]
JP Morgan Chase & Co. (JPM)
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Source: Forbes
The bottom line is stark : AI delivers measurable productivity gains of at the task level—yet 95% of enterprise AI pilots fail, aggregate economic statistics show negligible impact, and a Nobel laureate projects only total productivity growth over the next decade. This gap between micro-level wins and macro-level disappointment defines the central paradox facing investors, executives, and policymakers in 2026. The numbers tell a bifurcated story. Customer service agents using AI resolve 14% more issues per hour . GitHub Copilot users complete coding tasks 55% faster . BCG consultants finish work 25% quicker with 40% higher quality . But look at aggregate data: only 5% of U.S. firms have meaningfully adopted AI, and Bureau of Labor Statistics productivity growth—while healthy at 2.7% in 2024 —shows no clear AI signature. The Solow Paradox, first articulated in 1987 about computing, has returned: you can see AI everywhere except in the productivity statistics. The micro-macro disco
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