A Clark University division says it completed more work in a 32-hour week during a 50-day experiment that combined process changes, AI tools and a new incentive. Its vice-president Joe Manok says every measure improved by more than 20%, but the trial cannot show that AI caused the gains.
Watch Desk analysis
What happened
Manok describes the experiment in a Forbes Technology Council article. Staff worked four days a week on full pay, with a target of at least 120% of their previous output. The university says fewer than 10% worked extra hours, and that this work was excluded from its reported results.
The division reported nearly 40% more donor meetings, almost twice as many calls, handwritten notes and donor emails, and a 22% reduction in average gift-processing time. Of 32 staff members, 31 responded to a survey; all wanted the experiment to continue, while 81% wanted more AI resources. Manok says the trial changed several things at once, so it cannot identify which changes produced the results.
Why it matters
The figures offer a concrete example of an organisation testing whether productivity gains can mean shorter hours, rather than simply more work squeezed into the same day. But they are results from one division, reported by its vice-president, and not proof that AI or a four-day week would produce the same outcome elsewhere.
Our read
The most interesting part is not the AI label. It is the attempt to link efficiency with time returned to staff, while setting an output target and tracking service measures. Clark has approved a second phase through December, which may help show whether the gains last, though it still needs to disentangle the ingredients. “AI made us do it” would be a tidier conclusion, but not the one this experiment supports.
What to watch
- Whether the second phase sustains the reported output and service improvements.
- What Clark changes to distinguish the effects of AI, process redesign and the shorter week.
- Whether other organisations test explicit ways of sharing productivity gains with staff.
Discussion spark: If a workplace gets the same or better results in fewer hours, should staff share the gain through shorter weeks, or should employers decide how to use that time?
Sources and evidence
- How Sharing AI’s Time Savings Drives Productivity – Forbes (16 October 2026, 10:15 UTC)
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