## AI Adoption and Inequality

_IMF Working Papers, April 4, 2025_

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## Bibliographic details
- Authors: Emma J Rockall, Marina Mendes Tavares, Carlo Pizzinelli
- Published: April 4, 2025
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798229006828.001

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### Key findings on AI’s distributional effects
- There are competing narratives about artificial intelligence’s impact on inequality: some argue AI will exacerbate economic disparities, while others suggest it could reduce inequality by primarily disrupting high-income jobs.
- Using household microdata and a calibrated task-based model, the paper shows these narratives reflect different channels through which AI affects the economy.
- Unlike previous waves of automation that increased both wage and wealth inequality, AI could reduce wage inequality through the displacement of high-income workers.
- Two countervailing factors may offset potential reductions in wage inequality:
  - High-income workers’ tasks appear highly complementary with AI, potentially increasing their productivity.
  - High-income workers are better positioned to benefit from higher capital returns.
- When firms can choose how much AI to adopt, the wealth-inequality effect is particularly pronounced, because potential cost savings from automating high-wage tasks drive significantly higher adoption rates.
- Models that ignore firms’ adoption decisions risk understating the trade-off policymakers face between inequality and efficiency.

### Methods and data
- Data sources and approach:
  - Household microdata were used together with a calibrated task-based model.
- Model emphasis:
  - The calibrated task-based model incorporates firm-level adoption choices, highlighting adoption-driven amplification of wealth inequality.

### Policy-relevant implications and trade-offs
- Policymakers face a trade-off between efficiency (cost savings and productivity gains from AI adoption) and distributional outcomes (especially wealth inequality).
- Ignoring endogenous adoption choices in models can understate the magnitude of distributional consequences and the policy challenge.

### Publication and document metadata
- Title: AI Adoption and Inequality
- Authors: Emma J Rockall, Marina Mendes Tavares, Carlo Pizzinelli
- Date: April 4, 2025
- Series: IMF Working Papers; Working Paper No. 2025/068
- Issue: 068
- Volume: 2025
- Pages: 65
- DOI: https://doi.org/10.5089/9798229006828.001
- Stock No: WPIEA2025068
- ISBN: 9798229006828
- ISSN: 1018-5941

*Source: IMF Working Paper "AI Adoption and Inequality", Emma J Rockall, Marina Mendes Tavares, and Carlo Pizzinelli; April 4, 2025; Working Paper No. 2025/068; Pages: 65; DOI: https://doi.org/10.5089/9798229006828.001.*

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_Source: https://www.imf.org/en/publications/wp/issues/2025/04/04/ai-adoption-and-inequality-565729_