Impacto de la automatización en el empleo en industrias globales: un enfoque en los sectores de tecnología y fabricación de vehículos
Impact of automation on employment in global industries: A focus on the technology and vehicle manufacturing sectors
Abstract (en)
This study analyzes the multidimensional impact of automation on employment in the automotive and technology sectors between 2018 and 2023, with projections through 2030. Using a mixed-methods approach—combining quantitative analysis of 650 000 jobs lost and 510 000 new roles created with 15 qualitative case studies—the research reveals a dual effect in the labor market: for every industrial robot implemented, 4,2 traditional jobs are eliminated while 1,8 technology-intensive roles emerge, exacerbating skill polarization (OECD, 2019). Likewise, the digital transition in retail and banking has led to the collapse of indirect employment, eliminating 1,2 million ancillary jobs with a substitution ratio of 1:3,4 in favor of e-commerce (OIT, 2023). Geographic disparities are also evident: German automotive plants managed to retrain 92 % of their workforce, compared to 35 % in traditional U.S. manufacturing (IG Metall, 2023). The study proposes policy interventions, such as robot taxation and STEM education partnerships, to mitigate inequality. Projections indicate potential losses of between 852 000 and 1.1 million jobs by 2030 under current trends, underscoring the urgency of immediate action to align labor policies with the demands of Industry 4.0.
Abstract (es)
Este estudio analiza el impacto multidimensional de la automatización en el empleo dentro de los sectores automotriz y tecnológico entre 2018 y 2023, con proyecciones hasta 2030. Mediante una metodología mixta —que combina el análisis cuantitativo de 650 000 empleos perdidos y 510 000 nuevos roles creados con 15 estudios de caso cualitativos—, la investigación revela un efecto dual en el mercado laboral: por cada robot industrial implementado se eliminan 4,2 empleos tradicionales, mientras emergen 1,8 roles tecnológicos intensivos, lo que exacerba la polarización de habilidades (OECD, 2019). Asimismo, la transición digital en comercio minorista y banca ha provocado el colapso del empleo indirecto, eliminado 1,2 millones de empleos auxiliares con una relación de sustitución de 1:3,4 a favor del comercio electrónico (ILO, 2023). También se observan disparidades geográficas: las plantas automotrices alemanas lograron reconvertir al 92 % de su fuerza laboral, frente al 35 % en la manufactura tradicional estadounidense (Gaisenkersting, 2024). El estudio propone intervenciones políticas, como impuestos a los robots y alianzas educativas en STEM, para mitigar la desigualdad. Las proyecciones indican pérdidas potenciales de entre 852 000 y 1,1 millones de empleos para 2030 bajo las tendencias actuales, lo que urge la adopción de acciones inmediatas para alinear las políticas laborales con las demandas de la Industria 4.0.
References
Acemoglu, D., y Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188-2244. https://doi.org/10.1086/705716.
Anac. (2023). Tendencias del sector automotriz mundial al 2030.
Ángel Bonet. (2025). La industria del automóvil a 2030.
Arden University. (2022). 2030 workforce report. AM Online. https://www.am-online.com.
Beltrán Gaxiola, M. T. (2020). Impacto laboral por la automatización en Ford-Hermosillo. Revista Contad, 15(3), 45-67.
Boston Consulting Group. (2021a). Cobots en la industria automotriz: Transformación de la producción y eficiencia.
Boston Consulting Group. (2021b). The future of manufacturing: Collaborative robots and efficiency gains in production lines. BCG Insights. https://www.bcg.com.
Brynjolfsson, E. y McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company.
Bureau of Labor Statistics. (2023). Employment in artificial intelligence and automation: Trends and projections in the tech sector. U.S. Department of Labor. https://www.bls.gov.
Cognex Corporation. (s.f.). Sistemas de visión artificial para inspección en tiempo real. https://www.cognex.com.
Deacero Summit. (2024). Automatización en la fabricación automotriz. https://www.deacero.com.
Deloitte. (2022a). Impacto de la automatización en el sector automotriz: Reducción de empleos y creación de nuevos roles técnicos.
Deloitte. (2022b). The future of work: Automation, robotics, and industry employment trends. Deloitte Insights. https://www2.deloitte.com.
Ford Motor Company. (2023). Informe anual de automatización en plantas mexicanas. https://corporate.ford.com.
Gartner. (2021). Gartner forecasts chatbot adoption and impact on customer service jobs. Gartner Research.
Gaisenkersting, D. (2024). IG Metall aprueba 35.000 despidos y miles de millones de dólares en rebajas salariales en VW [Institucional]. World Socialist Website. https://www.wsws.org/es/articles/2024/12/23/2d33-d23.html
International Federation of Robotics (IFR). (2023a). Automation and employment trends: The impact of Industry 4.0 in manufacturing. IFR Reports. https://ifr.org.
International Federation of Robotics (IFR). (2023b). World Robotics Report: Robotic density and automation trends.
International Labour Organization (ILO). (2023). The impact of automation and digitalization on employment. https://www.ilo.org.
Japan Robotics Association. (2023). Advanced robotics and workforce transformation: Automation trends in Japan. Japan Robotics Industry Report. https://japanroboticsassociation.or.jp.
Lygo, C. (2022). Discurso en Foro Automotriz Europeo. En Memorias de Automatización Industrial (pp. 45-67). Springer.
MarketsandMarkets. (2024). Futuro de la industria automotriz.
McKinsey Global Institute. (2017). Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey & Company. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
McKinsey y Company. (2022a). The rise of intelligent logistics and warehouse automation.
McKinsey Global Institute. (2022b). Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation. McKinsey and Company.
McKinsey y Company. (2025). Mercado de software y electrónica automotriz.
MESbook. (s.f.). Industria 4.0 en el sector automotriz: Beneficios.
Organisation for Economic Co-operation and Development (OECD). (2019). OECD employment outlook 2019: The future of work. OECD Publishing. https://doi.org/10.1787/bb5fff5a-en
Organisation for Economic Co-operation and Development (OECD). (2021). Automation and labor productivity in manufacturing: Global analysis.
Organisation for Economic Co-operation and Development (OECD). (2023a). Employment outlook 2023: The future of work and productivity. OECD Publishing. https://doi.org/10.1787/bb5fff5a-en
Organisation for Economic Co-operation and Development (OECD). (2023b). Small and medium enterprises: Automation adoption and productivity outcomes.
Organisation for Economic Co-operation and Development (OECD). (2023c). Impacto de la automatización en empleos manufactureros. https://www.oecd.org
Organización Internacional del Trabajo. (2023). El futuro del trabajo en el sector minorista: La digitalización como motor de una recuperación económica sostenible y del trabajo decente (Informe para la discusión en la Reunión técnica sobre la digitalización en el sector minorista como motor de la recuperación económica y el trabajo decente, Ginebra, 25–29 de septiembre de 2023).
PwC. (2018). Cinco tendencias que transformarán el mercado del automóvil.
PwC. (2023). Economic impacts of automation on global labor markets: Projected job losses and creation by sector.
Schmitt, J. (2013, noviembre 19). Technology and inequality: Don't blame the robots. Economic Policy Institute. https://www.epi.org/publication/technology-inequality-dont-blame-the-robots/.
Schumpeter, J. A. (1942). Capitalism, socialism, and democracy. Harper & Brothers.
SERNAUTO. (2025). Las fábricas inteligentes en la industria automotriz.
Toyota Motor Corporation. (2025). Informe de innovación en plantas globales. https://www.toyota-global.com.
World Economic Forum. (2020). The future of jobs report 2020. https://www.weforum.org/reports/the-future-of-jobs-report-2020.
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