THE DEMAND FOR NEW PROFESSIONAL SKILLS AND THE FUTURE OF TRADITIONAL OCCUPATIONS IN THE AGE OF AUTOMATION AND ARTIFICIAL INTELLIGENCE

This article examines the impact of automation and artificial intelligence technologies on the labor market, professional skills, and the nature of traditional occupations. The central argument is that technological progress is accelerating the redistribution of tasks within occupations rather than eliminating entire professions as a whole. Through a comparative analysis of international research and reports, the study identifies differences in the assessment of automation risks, declining opportunities to gain initial professional experience, the need to verify AI-generated outputs, and challenges within reskilling systems. The article proposes an original model for assessing occupations based on task composition, human competencies, and the level of technological adaptability. It also develops practical recommendations for the labor market of Uzbekistan.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-04
DOI
https://doi.org/10.5281/zenodo.23959667
Primary Topic
Labor market dynamics and wage inequality
Type
article
Field-Weighted Citation Impact
0.00
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article

THE DEMAND FOR NEW PROFESSIONAL SKILLS AND THE FUTURE OF TRADITIONAL OCCUPATIONS IN THE AGE OF AUTOMATION AND ARTIFICIAL INTELLIGENCE

Sunnat Abdullayev, Abdurayimova Marjona
Zenodo (CERN European Organization for Nuclear Research)
Labor market dynamics and wage inequality
article

THE DEMAND FOR NEW PROFESSIONAL SKILLS AND THE FUTURE OF TRADITIONAL OCCUPATIONS IN THE AGE OF AUTOMATION AND ARTIFICIAL INTELLIGENCE

Sunnat Abdullayev, Abdurayimova Marjona
article en

Abstract

This article examines the impact of automation and artificial intelligence technologies on the labor market, professional skills, and the nature of traditional occupations. The central argument is that technological progress is accelerating the redistribution of tasks within occupations rather than eliminating entire professions as a whole. Through a comparative analysis of international research and reports, the study identifies differences in the assessment of automation risks, declining opportunities to gain initial professional experience, the need to verify AI-generated outputs, and challenges within reskilling systems. The article proposes an original model for assessing occupations based on task composition, human competencies, and the level of technological adaptability. It also develops practical recommendations for the labor market of Uzbekistan.

Zenodo (CERN European Organization for Nuclear Research)
Sarbon University (UZ)
Openalex Percentile: Top 11%
Labor market dynamics and wage inequality
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