Science and Technology Production
Article
Authorship
Eduardo Chávez Molina
;
RODRÍGUEZ DE LA FUENTE, JOSÉ JAVIER
Date
2026
Publishing House and Editing Place
Frontiers
Magazine
Frontiers in Sociology,
vol. 11
Frontiers
Summary
Information provided by the agent in
SIGEVA
This study investigates the automation risk in employment in four urban areas of Argentina, analysing the impacts of technological changes and the digital economy on the occupational structure. A survey (N = 426) was conducted using the Respondent Driven Sampling (RDS) technique. The analysis covered sectors with different levels of technological integration—high (e.g., software), medium (e.g., food), and low (e.g., textiles). An automation risk index was constructed based on job skills a...
This study investigates the automation risk in employment in four urban areas of Argentina, analysing the impacts of technological changes and the digital economy on the occupational structure. A survey (N = 426) was conducted using the Respondent Driven Sampling (RDS) technique. The analysis covered sectors with different levels of technological integration—high (e.g., software), medium (e.g., food), and low (e.g., textiles). An automation risk index was constructed based on job skills and tasks. The results indicate that professionals, scientists, managers, and technicians exhibit a lower risk of automation, while elementary and industrial occupations face a higher risk. Social and creative intelligence were identified as ‘bottlenecks’ in the face of automation, an aspect that we have emphasised in this analysis. The software and pharmaceutical sectors are more protected, unlike the textile and hotel industries. In addition, the use of Artificial Intelligence (AI) is more prevalent in lower-risk occupations, mainly for complex and skilled tasks, complementing human work. In conclusion, the study emphasises the need to understand these changes in order to comprehend and predict the future of the labor market. Skills involving emotional and creative intelligence offer robust protection against automation, although emerging generative AI could begin to impact tasks previously considered secure.
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Key Words
occupational structureautomationemploymentartificial intelligence