Andrew Yang Wants to Tax AI Instead of Workers

The tax code was written for an economy that assumed humans did the work. Andrew Yang thinks it's time to update the assumption.

In a Wednesday appearance on CNBC's Squawk Box, the Forward Party founder and former presidential candidate made a straightforward argument: "You tend to tax things that you want to discourage, that you want less of." His conclusion — if AI is displacing human labor, taxing labor while subsidizing nothing on the AI side is a policy that accelerates displacement rather than manages it.

"We should actually try to stop taxing labor," Yang told Squawk Box. The implicit second half of that sentence: and start taxing whatever is replacing it.

The Logic Is Sound

Yang's argument is structurally coherent. Income tax, payroll tax, Social Security contributions — the entire architecture of the American tax system is built on the premise that human employment generates the taxable surplus that funds public services. When a company replaces ten workers with an AI system, it stops paying the employer-side taxes those workers generated. The AI contributes nothing equivalent. The fiscal gap widens.

This isn't a hypothetical concern for 2040. It's a present condition accelerating now. Goldman Sachs estimated in 2023 that generative AI could automate tasks equivalent to 300 million full-time jobs globally. The McKinsey Global Institute has projected that up to 30% of current work hours in the US could be automated by 2030. The tax base those workers represent doesn't automatically migrate to new revenue sources when the workers are displaced.

Yang's proposal — variously framed over the years as an automation tax, a robot tax, or a value-added tax on AI-generated output — isn't new. Bill Gates floated a robot tax in 2017. The European Parliament considered and rejected a version of it in the same year. What's new is the timeline. The displacement that felt theoretical in 2017 is operational in 2026.

Why This Conversation Keeps Getting Deferred

The resistance to automation taxes comes from multiple directions, not all of them cynical. Economists argue that taxing productivity gains slows innovation and that historically, automation creates new categories of work even as it eliminates old ones. That's been true across industrial transitions for two centuries.

The honest question is whether this transition moves faster than the historical pattern. Previous waves of automation — mechanized agriculture, factory robotics, enterprise software — played out over decades, giving labor markets time to adapt. Generative AI is being deployed at a pace that compresses that adjustment window significantly. Whether new job categories emerge fast enough to absorb displaced workers is genuinely uncertain, and the people most certain it will work out tend to be the ones least exposed to the displacement.

Yang's framing cuts through the academic debate with a simple observation: we have a funding mechanism built on labor, and labor's share of economic activity is declining. Whatever you think about automation taxes specifically, that structural mismatch needs an answer.

What Marketers and Business Leaders Should Take From This

For growth professionals and CMOs, Yang's argument lands in a specific way. Marketing and content functions are among the categories experiencing AI displacement most directly and most visibly right now. Copywriters, designers, analysts, media buyers — these are not abstract future casualties. They are present workforce conversations happening inside real organizations.

The companies scaling AI the fastest are, in many cases, the same companies reducing headcount in the functions AI is replacing. That's a rational short-term business decision. It's also a contribution to the fiscal and social conditions Yang is describing.

This isn't a reason to stop using AI in your marketing operations. It is a reason to think about what responsible scaling looks like — how you communicate with affected teams, how you invest in reskilling, and whether your organization has a point of view on the policy environment it's helping to create.

The AI strategy conversation and the labor policy conversation are the same conversation, viewed from different altitudes. The businesses pretending otherwise are deferring a reckoning, not avoiding it.

Yang has been making versions of this argument since his 2020 presidential campaign, when Universal Basic Income was his signature proposal and most of the political establishment found it eccentric. The economic conditions he was describing then are more visible now. That doesn't make every policy prescription correct. It does suggest the underlying diagnosis was not wrong.

Source: Thibault Spirlet, Business Insider — "Andrew Yang says we should stop taxing workers — and start taxing AI"

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