Does artificial intelligence in companies lead to job cuts or a greater focus on employees? The current study “AI at Work” by the Nuremberg Institute for Market Decisions (NIM) and the St. Gallen Symposium (a platform for generational dialogue) clearly shows what managers prefer: They want to design jobs and roles in the future in such a way that people have more independence and can learn with AI. At the same time, people in the future working world should have tasks for which they need skills in which they are superior to AI. Only a few would like to see a reduction in staff as a result of AI transformation.
However, how viable this claim is in practice only becomes apparent when companies are examined more closely. Then it becomes clear that in reality, dealing with AI is often two-pronged.
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Info box: “AI at work” study 2026
The “AI at work” study was carried out by the Nuremberg Institute for Market Decisions (NIM) in cooperation with the St. Gallen Symposium. To this end, 585 international young managers under the age of 35 as well as 100 top managers from the world’s top-selling companies were surveyed in the period from January and February 2026. The topic of the survey is attitudes towards the future of work and the use of artificial intelligence. The aim of the study is to compare the perspectives of different leadership generations on transformation issues.
Unity when investing in employees
For the study, young managers under the age of 35 and experienced top managers were asked how they assess the use of artificial intelligence in companies. Despite different perspectives in many aspects, there is a clear common denominator among the almost 700 respondents: If AI makes work more efficient, the advantage should not simply remain with the company, but should benefit the employees.
In concrete terms, this means that the time and cost savings through AI should be used to further train employees, give them new tasks and prepare them for changing requirements. A large proportion of the managers surveyed are in favor of this: over 80 percent overall, including 87 percent of the younger ones and 81 percent of the older ones.
Within this focus on investing in employees, there are once again different priorities between the generations. Experienced managers (42 percent) rely more on further training and internal changes in the company than younger managers (29 percent). Young talents, on the other hand, place more value on making work more meaningful overall and more focused on human skills at 35 percent, while the figure for older managers is 22 percent.
Hardly any support for workforce reductions through AI
Things look completely different at the lower end of the scale. According to most executives, if companies become more efficient through AI, this should preferably not lead to job cuts. Only two percent of young managers and three percent of experienced managers believe that reducing staff numbers makes sense in order to remain competitive in the AI age.
Rather, they expect companies to take responsibility and actively support their employees when tasks change as a result of AI.
Managers’ priorities: This is how companies should use efficiency gains through AI
| priority | measure | Young managers (under 35 years old) | Older managers |
| 1. | Redesign jobs and roles (more autonomy, learning, using strengths) | 35 % | 29 % |
| 2. | Invest heavily in training and internal mobility | 29 % | 42 % |
| 3. | Reduce working hours with stable pay | 12 % | 11 % |
| 4. | Pass on profits to employees (wages, bonuses, etc.) | 11 % | 6 % |
| 5. | Achieve more output with the same workforce | 9 % | 16 % |
| 6. | Reduce staff to be competitive | 2 % | 3 % |
Reality: Between further development and job loss
As clear as the managers’ demands seem, the picture in corporate practice is mixed. Many companies are adapting the tasks and roles of their employees in parallel with the changes that come with artificial intelligence. At the same time, contrary to the priorities of managers, job cuts also play a noticeable role in reality.
A survey by the Munich Ifo Institute from June 2025 came to the conclusion that more than a quarter of companies assume that AI will lead to job cuts of an average of eight percent by 2030. Only around five percent expect additional jobs, while around two thirds expect no change in the number of employees.
The Ergo example shows that further development and job cuts often intertwine
The example of the Munich Re subsidiary Ergo (proper spelling ERGO) shows how closely this restructuring is linked to concrete personnel decisions. The insurance company consciously links the use of AI with planned job cuts. In February 2026, the company announced that it would cut around 1,000 jobs by 2030, affecting 200 employees annually. Behind this decision is the technological change through AI, which the company combines with great automation potential. While simple, repetitive activities in particular are being eliminated, new tasks and jobs are emerging in other areas.
At the same time, the company is pursuing a double strategy: In addition to cutting jobs and simple tasks, Ergo is investing in the qualification of its own workforce. An internal “reskilling academy” is intended to prepare employees for new tasks and, if possible, keep them in the company.
The example makes it clear: AI does not lead to a clear either/or, but rather to a parallel transformation. As some activities disappear, new ones emerge elsewhere, and companies are trying to manage this process. This pattern is also evident in other industries. According to media reports, Facebook’s parent company Meta announced that it was planning extensive layoffs, while at the same time the company was investing heavily in AI and building new structures.
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“AI at Work”: All study results at a glance
- Young managers see loss of skills as a key risk: 55 percent of younger managers versus 36 percent of older managers
- 40 percent of younger managers are critical of the loss of decision-making freedom (versus 22 percent of older managers).
- 54 percent of older managers cite handling sensitive data as the biggest challenge (versus 38 percent of younger managers).
- 87 percent of young and 81 percent of experienced managers want to reinvest profits through AI in employees.
- Only 2 percent of younger managers and 3 percent of older managers see workforce reductions as a priority measure.
- Young managers expect a high level of employer responsibility.
- Over 80 percent demand active support for employees in AI transformation.
Mara Marx is a volunteer at Human Resources.
