Are our jobs at risk?

Estimating the Effect of Artificial Intelligence on the Swiss Labor Market

Article summary

Part 2: Results of the study – effects on the Swiss economic sector and implications

Note: This blog post summarizes the article “Are Our Jobs at Risk? Estimating the Effect of Artificial Intelligence on the Swiss Labor Market”. Authors: Timon Jaeggi, Benjamin Schaefer, Christian Dietzmann, Reinhard Jung and Ulrich Matter


Suggested citation: Jaeggi, T., Schaefer, B., Dietzmann, C., Jung, R., & Matter, U. (2023). Are Our Jobs at Risk? Estimating the Effect of Artificial Intelligence on the Swiss Labor Market. In Academy of Management Proceedings (Vol. 2023, No. 1, p. 11166).

To analyze the impact of AI on the Swiss economic sector, a comprehensive qualitative and quantitative study on the exposure of individual professions to AI was conducted using a task-based view. For this purpose, a novel measure was developed to quantify the potential exposure of occupations, considering both potential substitution and complementarity effects (Jaeggi et al., 2023). This measure was compared with data on employment, education, and wages in Switzerland to examine the impact of AI at an aggregate level (Jaeggi et al., 2023). The detailed results, including graphs, are presented in the study. The theoretical basis was explained in the first part of this blog series.

Results of the study

The study found that a high match between tasks (determined by the required skills and abilities) and technology can lead to high substitution effects (Jaeggi et al., 2023). At the same time, the results show that the potential for substitution by AI is most prominent in occupations with low cognitive requirements (Jaeggi et al., 2023). However, a high match between task and technology can also lead to complementary effects by extending human senses, physical work, and human cognition, thus increasing efficiency (Jaeggi et al., 2023). It is noticeable that AI can primarily complement professions requiring high interpersonal interaction (Jaeggi et al., 2023). Companies with low digital skills must exploit both complementarity and substitution potential to maintain their competitiveness in the long term (Jaeggi et al., 2023). In addition, the results indicate whether AI will affect their jobs to their advantage or disadvantage (Jaeggi et al., 2023). If employees are exposed to a high substitution potential, training programs must be made aware of this in good time to teach the skills required (Jaeggi et al., 2023).

Impact on the Swiss economic sector

The study is one of the first to examine the Swiss economic sector by aggregating the results at the individual level to the sectors that are of great economic importance to Switzerland (Jaeggi et al., 2023). The results indicate that employees in accommodation and food services (AFS) are most affected by AI (Jaeggi et al., 2023). With an average exposure of 60 percent overall, occupations in this sector have the most significant potential for AI substitution (41 percent through embodied AI and 19 percent through software AI) (Jaeggi et al., 2023). In contrast, software AI can

Figure 1: Aggregated AI exposure measures for selected economic sectors

Note: The vertical axis indicates the aggregate share of employee tasks within a sector, where 1 represents 100 percent of tasks within that sector. The following economic sectors are considered: Accommodation and Food Services (AFS), Finance and Insurance (FI), Manufacturing (General, MA), Chemical Manufacturing (CM), Professional, Scientific and Technical Services (PST), and Health and Social Assistance (HSA). The figure is based on Jaeggi et al., 2023.

complement workers in an average of 34 percent of tasks in the finance and insurance (FI) and professional, scientific and technical services (PST) sectors (Jaeggi et al., 2023). Considering the potential impact of AI complementarity, occupations in these sectors may benefit the most from higher labor demand and wage increases (Jaeggi et al., 2023). When comparing the manufacturing (MA) and chemical (CM) sectors, it is noticeable that the distribution of AI exposures is comparatively similar, with minor differences in the substitution of embodied AI and the addition of software AI (Jaeggi et al., 2023). This difference may reflect the fact that chemical manufacturing (e.g., pharmaceuticals, pesticides, synthetic fuels, or synthetic materials), as opposed to general manufacturing (e.g., wood or textiles), tends to have a higher share of research and consequently a more significant share of information processing and scientific originality, which favors the complementary potential (Jaeggi et al., 2023). The health care and social assistance (HSA) sector is the least affected by AI technology, with around 41 percent of tasks unaffected (Jaeggi et al., 2023). Therefore, social and medical professions are likely to experience only minor AI-induced changes in the labor market in relative terms (Jaeggi et al., 2023).

The study also shows that AI substitution primarily affects employees at the lower end of the skills ladder (Jaeggi et al., 2023). Both the Swiss median wage and the level of education correlate negatively with AI substitution (Jaeggi et al., 2023). In contrast, AI complementarity is most pronounced at the upper qualification level and affects employees with higher wages and higher levels of education (Jaeggi et al., 2023). If the exposure measures are weighted with the absolute employment figures in Switzerland, it becomes apparent that 10 percent of the Swiss workforce is currently employed in low-skilled occupations strongly affected by AI substitution (Jaeggi et al., 2023). In addition, 48 percent of the Swiss workforce works in low to medium-skilled occupations that are only moderately affected (Jaeggi et al., 2023). In contrast, the section most affected by AI complementarity, around 61% of the Swiss workforce, comprises highly qualified occupational groups (Jaeggi et al., 2023).


Organizations and their management need to understand the impact and areas of influence of AI to proactively respond to digital trends and thus remain competitive (Jaeggi et al., 2023). For example, companies must understand how AI can be used to develop new business opportunities (Jaeggi et al., 2023). At the same time, examining the extent to which AI could impair the existing business model is essential (Jaeggi et al., 2023). In addition, technology directly impacts macroeconomic development and is of great importance for the future development of employment (Frey & Osborne, 2013). Policymakers should anticipate that technological advances in AI will transform specific industries and economic sectors (Jaeggi et al., 2023). As AI opens more and more cognitive areas of work (Brynjolfsson & McAfee, 2011; Frey & Osborne, 2013), economies that are highly characterized by industries involving such aspects (e.g., the service industry) will be particularly affected (Jaeggi et al., 2023). If AI leads to substituting occupations in an economy, policymakers must consider retraining and upskilling programs for the most affected workers to prevent massive technological unemployment (Felten et al., 2019, p. 2). Comprehensive policy measures also aim to mitigate the economic damage of AI substitution, including a universal basic income or extraordinary taxes for companies using AI technology (Bruun & Duka, 2018). Conversely, if the introduction of AI increases employment in most occupations, policymakers should provide additional support for AI progress through incentive programs (Jaeggi et al., 2023). Assuming substitution effects are directly linked to job losses, government institutions must mitigate or prevent the adverse effects on the population (Jaeggi et al., 2023).


Bruun, E., & Duka, A. 2018. Artificial Intelligence, Jobs and the Future of Work: Racing with the Machines. Basic Income Studies, 13(2).

Brynjolfsson, E., & McAfee, A. 2011. Race Against the Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy. Lexington, MA: Digital Frontier Press.

Felten, E. W., Raj, M., & Seamans, R. 2019. The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization. New York, NY: NYU Stern School of Business.

Frey, C. B., & Osborne, M. A. 2013. The Future of Employment: How Susceptible are Jobs to Computerization? Technological forecasting and social change, 114: 254-280.

Jaeggi, T., Schaefer, B., Dietzmann, C., Jung, R., & Matter, U. (2023). Are Our Jobs at Risk? Estimating the Effect of Artificial Intelligence on the Swiss Labor Market. In Academy of Management Proceedings (Vol. 2023, No. 1, p. 11166).

Benjamin Schaefer
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