Penn Wharton Budget Model
Summary
The Penn Wharton Budget Model estimates generative AI will gradually increase productivity and GDP, with peak contributions in the early 2030s and lasting economic impact.
Review
The Penn Wharton Budget Model provides a comprehensive analysis of generative AI's potential economic impact, using a nuanced task-based framework to estimate productivity gains. By examining AI's exposure across different occupational categories, the study reveals that approximately 40% of current labor income could be substantially affected by AI, with occupations around the 80th percentile of earnings being most exposed. The methodology combines estimates of AI task exposure, cost savings, and technology adoption patterns, projecting a peak AI contribution to total factor productivity (TFP) growth of 0.2 percentage points in 2032, eventually stabilizing at a persistent 0.04 percentage point boost. This translates to cumulative GDP level increases of 1.5% by 2035, nearly 3% by 2055, and 3.7% by 2075. The researchers emphasize caution, noting these projections are based on limited initial data and could change significantly with technological developments.
Key Points
- 40% of current labor income potentially exposed to AI automation
- Peak AI productivity contribution of 0.2 percentage points expected in 2032
- Projected cumulative GDP increase of 3.7% by 2075