AI Skill Demand and Employment Stratification in Copyright-Intensive Information Industries: Evidence from Job Postings and Industry-Level Employment Data.

Autor/inn/en	Palmedo, Michael; Lutes, Brent; Safner, Ryan
Titel	AI Skill Demand and Employment Stratification in Copyright-Intensive Information Industries: Evidence from Job Postings and Industry-Level Employment Data. Gefälligkeitsübersetzung: Nachfrage nach KI-Kompetenzen und Beschäftigungsstratifizierung in urheberrechtsintensiven Informationsbranchen: Erkenntnisse aus Stellenanzeigen und Beschäftigungsdaten auf Branchenebene.
Quelle	In: Work and occupations, 53 (2026) 3, S. 707-744 PDF als Volltext Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	1552-8464
DOI	10.1177/07308884261447535
Schlagwörter	Verdrängung; Künstliche Intelligenz; Urheberrecht; Fachkenntnisse; Geistige Arbeit; Automatisierung; Beschäftigungseffekt; Unterhaltungsindustrie; Arbeitskräftebedarf; Qualifikation; Qualifikationsbedarf; Stellenausschreibung; Informationstechnischer Beruf; Informationswirtschaft; Alter; Auswirkung; Geschlechtsspezifik; Kulturwirtschaft; USA
Abstract	"This paper examines how employer demand for workers skilled in the use of artificial intelligence (AI) is associated with employment patterns in copyright-intensive industries within the U.S. information sector. Using panel data from the Census Bureau's Quarterly Workforce Indicators combined with data on AI-related job postings, we analyze how the relationship between employer demand for AI skills and employment levels varies across worker groups between 2018 and 2024. Furthermore, we document changes in this relationship following the widespread introduction of generative AI in late 2022. We find that employment in copyright-reliant information industries declined relative to other industries after late 2022, and that the association between AI-related job postings and employment is highly heterogeneous. Initial findings indicate that employment relationships were negative or statistically insignificant for workers who had not completed a four-year college degree, for women, and for the youngest and oldest age cohorts. A positive relationship existed for college educated workers, men, and prime-age workers, though this weakened in the periods after the introduction of generative AI. These findings provide early insights into how demand for generative AI skills may reshape labor market stratification within creative and information-intensive industries and underscore the importance of examining technological change in future research." The study refers to the period 2018-2024 (Author's abstract, IAB-Doku).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2026/4