How AI Could Boost the Economy: Wharton Projects 3.7% GDP Increase by 2075
A new analysis from the University of Pennsylvania's Wharton School reveals that generative artificial intelligence could deliver substantial long-term economic gains, but the biggest productivity boosts may come sooner than expected.
The Numbers That Matter
Penn Wharton Budget Model researchers estimate AI will increase productivity and GDP by:
- 1.5% by 2035
- Nearly 3% by 2055
- 3.7% by 2075
The most dramatic impact on annual productivity growth will peak in 2032, contributing 0.2 percentage points before gradually tapering off as AI adoption saturates across the economy.
Who's Most at Risk—and Most Likely to Benefit
The study reveals a surprising pattern: middle-to-upper-middle earners face the greatest exposure to AI automation. Workers around the 80th percentile of earnings could see about half their tasks automated, while both the highest and lowest earners are relatively protected.
Most exposed occupations include:
- Office and administrative support (75.5% of tasks)
- Business and financial operations (68.4% of tasks)
- Computer and mathematical roles (62.6% of tasks)
Least exposed sectors:
- Construction and extraction (8.9% of tasks)
- Building and grounds maintenance (2.6% of tasks)
The AI Adoption Timeline
Drawing parallels to previous technology rollouts like the internet and smartphones, researchers project AI will follow a familiar pattern. Current data shows 26.4% of workers already use generative AI at work—adoption rates that match or exceed early adoption of personal computers.
However, early signs suggest the labor market is already responding. Employment has stagnated in highly AI-exposed occupations, with jobs that can be performed entirely by AI seeing a 0.75% decline since 2021.
What This Means for Your Future
The analysis suggests AI's economic impact will be material but not transformative. While the technology promises meaningful productivity gains, these benefits will be concentrated in information-processing jobs rather than manual labor or high-level strategic roles.
The researchers caution their projections are based on limited early data and could change significantly as AI technology continues to evolve.
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