# The risks and bottlenecks to automation in employment in Argentina. New impacts on the occupational structure in selected economic sectors

## TL;DR

This study explores how automation affects jobs in Argentina, showing that some sectors and roles are more at risk than others.

## Contribution

The study introduces an automation risk index and highlights social and creative intelligence as key bottlenecks to automation.

## Key findings

- Elementary and industrial occupations face higher automation risk compared to professionals and technicians.
- Social and creative intelligence are identified as critical factors in resisting automation.
- AI is more prevalent in lower-risk, skilled occupations, complementing human work.

## Abstract

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.