Abstract This study explores the transformative impact of Artificial Intelligence (AI) on labor markets, employee workplace, particularly focusing on job roles, demographic variables and job satisfaction. The research examines AI's historical development, its adoption across various sectors, and its dual role as both a job creator and displacer. Through a detailed analysis of AI's application in manufacturing and finance, the study highlights how AI-driven automation is reshaping job structures, enhancing productivity, and creating new employment opportunities as well as noble AI-related job functions and influencing employee attitude towards job. The findings underscore the importance of understanding AI's multifaceted impact on job satisfaction and the necessity for proactive measures in workforce training and development to mitigate potential negative consequences on employee well-being.

Intelligenza Artificiale e Soddisfazione sul Lavoro: Valutazione delle Prospettive dei Dipendenti

IKROMOV, AKHRORKHON
2023/2024

Abstract

Abstract This study explores the transformative impact of Artificial Intelligence (AI) on labor markets, employee workplace, particularly focusing on job roles, demographic variables and job satisfaction. The research examines AI's historical development, its adoption across various sectors, and its dual role as both a job creator and displacer. Through a detailed analysis of AI's application in manufacturing and finance, the study highlights how AI-driven automation is reshaping job structures, enhancing productivity, and creating new employment opportunities as well as noble AI-related job functions and influencing employee attitude towards job. The findings underscore the importance of understanding AI's multifaceted impact on job satisfaction and the necessity for proactive measures in workforce training and development to mitigate potential negative consequences on employee well-being.
ENG
IMPORT DA TESIONLINE
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14240/113400