{"id":{"repo_id":"brazil-ufba","oai_identifier":"oai:repositorio.ufba.br:ri/43989"},"canonical_url":"https://search.dev.ndltd.org/etd/brazil-ufba/oai:repositorio.ufba.br:ri/43989","repository":{"repo_id":"brazil-ufba","name":"Brazil UFBA","base_url":"https://repositorio.ufba.br/oai/request"},"display":{"title":"Inovações disruptivas no mercado de trabalho brasileiro: panorama atual e perspectivas","abstract":"The implementation of generative AI and the automation process of current disruptive technologies benefit consumers through increased supply, diversification, and lower prices of goods and services. However, these advances can also generate negative impacts: structural unemployment, wage reductions, and a decrease in the labor force participation rate. This work derives an indicator of exposure to automation (the IEA) aiming to estimate a macroeconomic analysis of the impacts of AI and automation in ten economic sectors in Brazilian states from 2022 to 2024, using the Brazilian labor market as a case study and drawing a parallel with the economic literature. The results show that the sectors most intensive in routine tasks (manufacturing, construction, agriculture, and transportation) are the most exposed to automation, while those intensive in abstract and cognitive tasks (public administration, health, and education) are the least impacted. On the other hand, when AI complements work, it mainly impacts the service sector, which is intensive in routine cognitive tasks. Furthermore, women in skilled occupations tend to be less negatively impacted than men by the adoption of technology. And there are regional disparities, with higher levels of exposure to AI and automation observed in different sectors by state.","abstract_html":"The implementation of generative AI and the automation process of current disruptive technologies benefit consumers through increased supply, diversification, and lower prices of goods and services. However, these advances can also generate negative impacts: structural unemployment, wage reductions, and a decrease in the labor force participation rate. This work derives an indicator of exposure to automation (the IEA) aiming to estimate a macroeconomic analysis of the impacts of AI and automation in ten economic sectors in Brazilian states from 2022 to 2024, using the Brazilian labor market as a case study and drawing a parallel with the economic literature. The results show that the sectors most intensive in routine tasks (manufacturing, construction, agriculture, and transportation) are the most exposed to automation, while those intensive in abstract and cognitive tasks (public administration, health, and education) are the least impacted. On the other hand, when AI complements work, it mainly impacts the service sector, which is intensive in routine cognitive tasks. Furthermore, women in skilled occupations tend to be less negatively impacted than men by the adoption of technology. And there are regional disparities, with higher levels of exposure to AI and automation observed in different sectors by state.","abstract_has_math":false,"creators":["Jesus, Welerson Silvio Souza de"],"institution":"Universidade Federal da Bahia","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12-18","date_published":"2025-12-18","updated_at":"2026-07-27T22:07:50Z","subjects":["Inteligência artificial","Automação","Mercado de trabalho"],"languages":["por"],"rights":["Acesso Aberto"],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/3.0/br/"],"identifier_entries":[]},"links":{"outbound_url":"https://repositorio.ufba.br/handle/ri/43989","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Jesus, Welerson Silvio Souza de"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-02-04T14:56:23Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-02-04T14:56:23Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-12-18"]},{"key":"dc:publisher","label":"Institution","values":["Universidade Federal da Bahia"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Faculdade de Economia"]},{"key":"dc:type","label":"Dc Type","values":["Trabalho de Conclusão de Curso"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Inteligência artificial","Automação","Mercado de trabalho"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["por"]},{"key":"dc:rights","label":"Dc Rights","values":["Acesso Aberto"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by-nc-nd/3.0/br/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://repositorio.ufba.br/handle/ri/43989"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The implementation of generative AI and the automation process of current disruptive technologies benefit consumers through increased supply, diversification, and lower prices of goods and services. However, these advances can also generate negative impacts: structural unemployment, wage reductions, and a decrease in the labor force participation rate. This work derives an indicator of exposure to automation (the IEA) aiming to estimate a macroeconomic analysis of the impacts of AI and automation in ten economic sectors in Brazilian states from 2022 to 2024, using the Brazilian labor market as a case study and drawing a parallel with the economic literature. The results show that the sectors most intensive in routine tasks (manufacturing, construction, agriculture, and transportation) are the most exposed to automation, while those intensive in abstract and cognitive tasks (public administration, health, and education) are the least impacted. On the other hand, when AI complements work, it mainly impacts the service sector, which is intensive in routine cognitive tasks. Furthermore, women in skilled occupations tend to be less negatively impacted than men by the adoption of technology. And there are regional disparities, with higher levels of exposure to AI and automation observed in different sectors by state."]},{"key":"dc:title","label":"Title","values":["Inovações disruptivas no mercado de trabalho brasileiro: panorama atual e perspectivas"]}]}],"canonical_facts":{"dc:creator":["Jesus, Welerson Silvio Souza de"],"dc:date.accessioned":["2026-02-04T14:56:23Z"],"dc:date.available":["2026-02-04T14:56:23Z"],"dc:date.issued":["2025-12-18"],"dc:description.abstract":["The implementation of generative AI and the automation process of current disruptive technologies benefit consumers through increased supply, diversification, and lower prices of goods and services. However, these advances can also generate negative impacts: structural unemployment, wage reductions, and a decrease in the labor force participation rate. This work derives an indicator of exposure to automation (the IEA) aiming to estimate a macroeconomic analysis of the impacts of AI and automation in ten economic sectors in Brazilian states from 2022 to 2024, using the Brazilian labor market as a case study and drawing a parallel with the economic literature. The results show that the sectors most intensive in routine tasks (manufacturing, construction, agriculture, and transportation) are the most exposed to automation, while those intensive in abstract and cognitive tasks (public administration, health, and education) are the least impacted. On the other hand, when AI complements work, it mainly impacts the service sector, which is intensive in routine cognitive tasks. Furthermore, women in skilled occupations tend to be less negatively impacted than men by the adoption of technology. And there are regional disparities, with higher levels of exposure to AI and automation observed in different sectors by state."],"dc:identifier.uri":["https://repositorio.ufba.br/handle/ri/43989"],"dc:language":["por"],"dc:publisher":["Universidade Federal da Bahia"],"dc:publisher.department":["Faculdade de Economia"],"dc:rights":["Acesso Aberto"],"dc:rights.uri":["http://creativecommons.org/licenses/by-nc-nd/3.0/br/"],"dc:subject":["Inteligência artificial","Automação","Mercado de trabalho"],"dc:title":["Inovações disruptivas no mercado de trabalho brasileiro: panorama atual e perspectivas"],"dc:type":["Trabalho de Conclusão de Curso"]},"updated_at":"2026-07-27T22:07:50Z"}