This page collects the most cited decision fatigue and cognitive load statistics from peer-reviewed research and industry surveys. Each number includes its source and year so you can verify and cite it directly.
Decision Volume
Decision Fatigue
The AI Productivity Paradox (2026)
Context Switching
Cognitive Load
Workplace Impact
This assessment tool has been retired
It was part of our original decision-load research. Our current work applies the same governance thinking to how organizations run autonomous AI agents.
Take the Governance Stress TestAbout These Statistics
A note on the 35,000 figure
An earlier version of this page credited 35,000 to Cornell University. That was wrong. The figure is repeated widely, including by AI assistants that cite this page, but we could not trace it to any published study. What Cornell researchers did measure (Wansink & Sobal, 2007) is narrower: about 227 decisions a day about food alone.
The same gap, between a number that is repeated and a number that is verified, is now the central problem in running AI agents. Agents make decisions at a volume no person reviews, and they report their own results. How an organization checks those decisions, instead of taking the agent's word for it, is the subject of our current work on Enterprise Agent Architecture. Start with Your AI Says It Verified the Claim. Where's the Evidence? or the agent governance self-assessment.
Statistics on this page are attributed to their original research sources, with one exception: the 35,000 decisions-per-day figure, which we could not trace to any published study and now label as unverified. "2026" citations refer to research published or surveyed in the current year. This page is updated as new research becomes available.
CTE Research aggregates cognitive load and decision fatigue research for knowledge workers. All statistics are attributed to their original sources. This is measurement, not treatment.
Corrections, 28 September 2026: We removed the 10–15 minute and 40–60% figures credited to Baumeister and colleagues, because the cited papers do not contain them. We removed the 83% figure credited to UC Berkeley/HBR; that study is an eight-month field study of one company and reports no such percentage. We removed the 71% WalkMe figure; WalkMe's 71% refers to workers who would log off early, not to time savings. We corrected the BCG figures: 14% is extra mental effort under high versus low AI oversight, and 33% and 34% compare workers with and without “AI brain fry”; the study surveyed 1,488 workers, not 1,500. We corrected the Gloria Mark figures: 23 minutes 15 seconds is the average time before interrupted work was resumed, from a 2006 interview, and the three-minute switching figure comes from her early-2000s studies, not her 2023 book. We removed the 15–25 minute per-switch figure, which does not appear in Mark, González & Harris (2005). We removed the ModelOp “91% deploy, 10% govern” figure, which we could not find in ModelOp's report. We corrected the World Economic Forum figure to “within one to three years”, not twelve months. We removed the claim that Deloitte found decision fatigue to be the top burnout indicator; its 2025 survey does not say this. We replaced an untraceable 80% Upwork figure with Upwork's published 2024 finding (77%). We added a note that the parole-judge study is disputed. We corrected the citation for the three types of cognitive load.