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Sen. Bernie Sanders argues that if AI and automation make workers more productive, the gains should help workers through shorter hours—not simply cost them their jobs. His proposal points to a 32-hour workweek, or four eight-hour days. But that is a policy argument, not evidence that AI has already produced enough measured gains to fund a four-day week.
What did Bernie Sanders say about AI and a four-day workweek?
In a Joe Rogan interview reported by TechCrunch on June 25, 2025, Sanders argued that workers should share the benefits when technology raises productivity. TechCrunch quoted him: “You are a worker, your productivity is increasing because we give you AI, right? Instead of throwing you out on the street, I’m gonna reduce your workweek to 32 hours.” He also said, “Let’s use technology to benefit workers,” including by giving them more time for family, friends, and education.
Business Insider reported that the episode was released Tuesday, June 24, 2025, and quoted Sanders making the same argument. The wording above is attributed to the outlets’ reporting; it is not presented as a transcript independently verified against the original audio.
What would a 32-hour week mean?
Sanders introduced the Thirty-Two Hour Workweek Act the previous year, according to Business Insider. As that outlet describes the bill, it would require overtime pay for hours worked beyond 32 and phase in the change over four years. A 32-hour schedule could mean four eight-hour days, but the reporting does not establish that every employer would use that exact daily arrangement.
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The bill’s current status is not established by the cited reporting. The proposal also does not, by itself, demonstrate that employers could keep output, wages, and service coverage unchanged in every occupation while reducing hours.
Do the cited four-day-week examples show that AI can pay for shorter hours?
No. The examples reported by TechCrunch concern four-day-week trials or policies, not a demonstrated causal link between AI adoption and shorter hours.
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| Example | What the report says | What it does not establish |
|---|---|---|
| UK pilot in the latter half of 2022 | TechCrunch reported that 61 companies, representing around 2,900 workers, took part. Among the 23 companies that shared financial data, average revenue rose 1.4% from the beginning to the end of the trial. | The revenue figure covers only those 23 companies, not all 61. The underlying trial report was linked in the article but could not be independently checked here; the figures are attributable to TechCrunch’s 2025 reporting. |
| Microsoft Japan pilot in 2019 | TechCrunch reported a 40% increase in productivity. | The article does not specify the productivity measure or study design. It is not an AI-effect finding. |
| Kickstarter | TechCrunch reported the company had operated on a four-day workweek since 2021. | The cited reporting does not give a comparable productivity or revenue result for Kickstarter. |
These examples may inform discussion about shorter schedules, but they do not show that AI generated the gains, that the results apply across sectors, or that a 32-hour schedule can be adopted without trade-offs.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Will AI actually make the eight-hour workday shorter?
That depends on choices by employers and policymakers, not just on whether AI tools increase productivity. In the cited reporting, no quantified AI-caused productivity gain is provided. Sanders’s position is a proposal for how gains should be shared if they occur: workers should receive some benefit in time, rather than productivity gains translating only into reduced headcount or greater output.
Whether a shorter week is workable depends on what counts as productivity and what an organization must keep doing. A revenue increase, a broad productivity claim, and continued service coverage are different measures. The cited reports do not provide enough comparable information about trial methods, pay treatment, schedules, or industry requirements to rank the examples or predict results for a particular workplace.
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