Historical milestone · 2025
Generative AI at Work
Reviewed through September 18, 2026
2025 · Historical milestone
Generative AI at Work
- Era
- 2020s
- Theme
- Human–AI interaction & adoption
- Evidence form
- Large field study
- School / paradigm
- Field experiment / labor economics
- Institution / context
- Stanford University; MIT
- Researchers
- Erik Brynjolfsson; Danielle Li; Lindsey Raymond
School of thought
Human augmentation and sociotechnical systems
Matched on representative researcher.
Intelligence and value reside in the joint human-machine-organization system, not the automation alone.
Critique. Human behavior and institutions are context-dependent; laboratory usability may not predict long-run value or harm.
Modern descendants. Copilots, agent supervision, workflow redesign, adoption metrics, and human-centered AI.
Understand
Plain-language record, transferred from the reviewed source module.
Theory or experimental setup. Studied the introduction of a generative assistant among 5,172 customer-support agents and compared productivity and worker-experience outcomes.
Result / historical claim. Reported an average 15 percent increase in resolutions per hour with larger gains for less experienced workers.
Apply
Professional implication, only where the reviewed record states one.
The checked-in record does not state a separate professional application for this entry. The topic page places it in the wider research lineage: Human–AI interaction and adoption.
Verify
Evidence status, stated limitations, and the external sources this record actually carries.
Evidence form. Large field study
Limitation / debate. One firm, occupation, workflow, and tool do not establish economy-wide or long-run labor effects.
Source status. The source link below is the verified link our reviewed topic research already carries for this milestone.
Reproduce
A reproduction tutorial is linked only when one exists for this exact record.
A reproduction tutorial is not yet available for this entry. The closest reviewed material is Human–AI interaction and adoption.
Cite or share
APA-like: This historical record carries a year only, and no author or publisher of record in the checked-in data. An APA reference would have to invent that metadata.
BibTeX: BibTeX requires an author and publication venue. Historical lineage entries store a narrative record and its source link, not structured authorship, so the field would be fabricated.