Elena Patel and Aparna Mathur compare five leading proposals to tax AI, from a training compute tax to levies on AI use
Brookings commentary by Elena Patel and Aparna Mathur compares five leading proposals to tax AI, from taxes on training compute to levies on AI use. It argues that federal income and payroll taxes, which fund about 85% of federal receipts, could erode if AI shifts income from workers to capital. The authors note AI-specific taxes are politically easy to explain but not economically necessary, since broader reforms such as a VAT, carbon tax, or corporate cash-flow tax could address similar concerns. The excerpt is partial and the full comparison of proposals is not included.
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Brookings commentary by Elena Patel and Aparna Mathur compares five leading proposals to tax AI, from taxes on training compute to levies on AI use. It argues that federal income and payroll taxes, which fund about 85% of federal receipts, could erode if AI shifts income from workers to capital. The authors note AI-specific taxes are politically easy to explain but not economically necessary, since broader reforms such as a VAT, carbon tax, or corporate cash-flow tax could address similar concerns. The excerpt is partial and the full comparison of proposals is not included.
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Key findings from the stored brief
- Individual income and payroll taxes generate roughly 85% of federal tax receipts, drawing heavily on worker income.
- Three arguments for taxing AI: eroding tax base, AI infrastructure costs borne by non-users, and possibly excessive AI investment.
- The authors state that achieving these goals does not strictly require an AI-specific tax.
- A training compute tax would have narrow reach, with few taxpayers, but enforcement relies on self-reported data.
Source claims not independently checked; the supplied text is a partial excerpt that cuts off before the comparison of the later proposals.
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Evidence & sources
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In an Oct 27 Brookings piece, Elena Patel (Urban-Brookings Tax Policy Center) and Aparna Mathur (American Enterprise Institute) set out five leading proposals to tax AI, including a training compute tax, and compare timing, revenue, ease of collection and trade-offs. They note income and payroll taxes are about 85% of federal receipts. Authors' analysis, not policy action; may suit Resources.
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Why this may matter
Lawmakers are proposing AI-specific taxes, and how AI shifts income between workers and capital bears directly on future federal revenue and the funding of programs for displaced workers.
Limits and open questions
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