# Four Day For AI

> Four Day For AI advocates a four-day, 32-hour standard working week, the same weekly pay and benefits, and a worker voice in technology adoption.

Canonical site: https://4day4ai.org/
Language: English. Updated: 2026-10-31 (America/Los_Angeles).

## The movement and demand

A movement for workers to share in AI productivity gains through a shorter working week with no loss of pay or benefits.

- 4 days and 32 standard working hours per week.
- Maintain weekly pay and benefits when standard weekly hours fall.
- Fewer weekly hours, not forty hours compressed into four days.
- Workers should participate in decisions about how AI is introduced and how its gains are shared.

The campaign defines a proposed standard; detailed transition and sector arrangements are not yet specified.

## Pages and structured data

- [Campaign and demand](https://4day4ai.org/): The public movement page.
- [Landing-page evidence](https://4day4ai.org/#evidence): The research currently presented on the campaign page.
- [Movement JSON](https://4day4ai.org/movement.json): Policy definitions, resource links, sharing text and checked evidence summaries.
- [Evidence case file](https://4day4ai.org/evidence.json): Full checked records, including populations, methods, results, limitations, source IDs and verification dates. The collection can include research beyond the landing page.
- [Share the message](https://4day4ai.org/#share): Copyable campaign text and a QR code for the canonical site.

## Checked evidence

- [The Productivity–Pay Gap](https://www.epi.org/productivity-pay-gap/) — US net productivity grew 93.7%; typical workers' hourly compensation grew 32.7% from 1979 Q4 to 2026 Q2. US inflation-adjusted series; compensation covers private-sector production and nonsupervisory workers, while productivity covers the total economy. Case ID: `epi-productivity-pay-2026-09`. Checked 2026-10-31.
- [Work time reduction via a 4-day workweek finds improvements in workers’ well-being](https://www.nature.com/articles/s41562-025-02259-6) — A six-month shorter-week study found improved self-reported well-being among 2,896 employees in 141 organizations, a pattern absent in 12 control organizations. Nonrandomized, income-preserving trials in six countries; schedules and hours varied. Case ID: `nhb-2025-four-day-wellbeing`. Checked 2026-10-31.
- [Generative AI at Work](https://academic.oup.com/qje/article/140/2/889/7990658) — AI assistance increased issues resolved per hour by 15% on average in a study of 5,172 customer-support agents at one firm and its contractors. Mostly Philippines-based agents serving US customers; effects varied by experience. Case ID: `qje-2025-generative-ai-at-work`. Checked 2026-10-31.

## Interpretation and provenance

The 32-hour week is a policy demand. These studies do not establish that AI already funds this reduction in every job or industry.

A growing selection of relevant evidence, not a systematic review or an exhaustive account of the literature. The recorded claims, scope and citations have been checked against the listed sources. Verified does not mean independently replicated or universally applicable.

Empirical findings describe the studied tasks, workers, places and periods; the movement's demand is a separate policy position. Task productivity, economy-wide productivity, hourly compensation and worker well-being are different measures. The evidence does not support a universal tenfold productivity claim or a claim that every workplace can already move to 32 hours at unchanged weekly pay. A source's publication date, data period and the project's verification date are recorded separately.

Only verified records appear in the public case file. When citing a finding, include its source, population, measure and data period where supplied; use the case ID to match the summary to its full record. Source publication/update dates and project verification dates are distinct.