Ersetzbar am Arbeitsplatz: Ifo: KI-Effekt am Arbeitsmarkt - Berufseinsteiger leiden

A new early indicator from the Ifo Institute suggests that the rise of Artificial Intelligence (AI) in many companies is leading to worse job prospects for new entrants into the workforce. However, the Munich economists have not observed large-scale job losses due to AI yet. Ifo President Clemens Fuest and his team have published the new AI early indicator to measure the effects of the increasing spread of AI on the labor market.

They compare employment and new hires in 140 occupations and relate them to the replaceability of human tasks through AI.

Not only IT workers are easily replaceable; the full-time employment of 20-24-year-olds has dropped by 14% in the most AI-exposed professions since 2022, falling from approximately 279,000 to 239,000. At the top of the list of occupations with a high share of easily automated tasks are data collection and text processing, followed by software developers, accountants, database and network technicians, and writers and journalists.

Ifo President Clemens Fuest stated, "We do not see a broad job loss due to AI at the moment," but new entrants into the workforce will first notice the changes.

However, the AI effects are not solely negative. AI impacts on the labor market can also take opposing directions, according to Fuest and his co-authors. On one hand, there is automation, and on the other, augmentation: AI can support and make human workers more productive. In terms of the overall labor market, employment in AI-exposed occupations has even grown by 1.8% since 2022, while it has decreased by 6.4% in non-exposed occupations.

Co-author Oliver Falck views the job loss among new entrants as a warning sign for the labor market. However, managers must not feel secure; AI could also significantly streamline the work of business leaders and CEOs. Non-AI-exposed occupations mainly include manual trades and other manual tasks. These include kitchen helpers, although manual workers such as construction workers, carpenters, painters, building cleaners, farmers, and household managers are also at the bottom of the list.

The researchers emphasize that the new AI indicator from the institute should not be seen as a single cause explanation. It does not mean that AI alone causes the observed effects; other factors such as demographic changes and longer training periods could also play a role.