The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector

Thesis title: The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector
Author: Do, Thi Ngoc Huyen
Thesis type: Diploma thesis
Supervisor: Mazouch, Petr
Opponents: Lichard, Tomáš
Thesis language: English
Abstract:
This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change.
Keywords: Technological change; employment dynamics; workforce transformation; panel data analysis
Thesis title: The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector
Author: Do, Thi Ngoc Huyen
Thesis type: Diplomová práce
Supervisor: Mazouch, Petr
Opponents: Lichard, Tomáš
Thesis language: English
Abstract:
This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change.
Keywords: Technological change; workforce transformation; panel data analysis; employment dynamics

Information about study

Study programme: Economic Data Analysis/Data Analysis and Modeling
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Economic Statistics

Information on submission and defense

Date of assignment: 8. 4. 2025
Date of submission: 5. 5. 2025
Date of defense: 2025

Files for download

The files will be available after the defense of the thesis.

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