The Projected Impact of Generative AI on Future Productivity Growth — Penn Wharton Budget Model
This Wharton Budget Model article analyzes how generative AI adoption may affect long-term productivity growth, weighing the potential efficiency gains against workforce challenges and measurement complexities. Connect with Cyber Security Consulting Ops to discuss what these shifts could mean for your business strategy.
Generative AI is expected to increase productivity and GDP by approximately 1.5% by 2035, nearly 3% by 2055, and 3.7% by 2075. The strongest boost to annual productivity growth is anticipated in the early 2030s, with a peak contribution of 0.2 percentage points in 2032.
Around 40% of current GDP could be significantly impacted by generative AI, with occupations at the 80th percentile of earnings being the most exposed. Approximately half of the work in these high-earning jobs is susceptible to automation by AI.
Long-term Effects of AI Adoption
While AI's boost to productivity growth is projected to peak in the early 2030s, its long-term effect will result in a permanent increase in total factor productivity (TFP) levels, estimated to be around 1.5% higher by 2035, 3% higher by 2055, and 3.7% higher by 2075 compared to a scenario without AI.
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The Projected Impact of Generative AI on Future Productivity Growth — Penn Wharton Budget Model
published by Cyber Security Consulting Ops
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