(de-news.net) – Artificial intelligence (AI) is increasingly shaping investment decisions, public finances, corporate strategy and labor markets, with effects already visible across Germany and other developed economies. The transition, however, is far from uniform. While companies and investors see potential productivity gains and new areas of growth, entry-level workers, particular occupations and the systems that finance public services are facing growing pressure. The emerging picture is therefore less one of a single, economywide disruption than of a shift whose effects vary substantially by sector, occupation and institution.
A significant economic risk identified by the CDU-affiliated Economic Council is the potential decoupling of productivity from wage labor. If automation reduces the amount of human labor required and wages subsequently grow more slowly than overall economic output, the contribution base supporting Germany’s social insurance system could become smaller relative to the country’s economic performance. Wolfgang Steiger, the council’s secretary-general, has consequently argued that the resilience of Germany’s tax and social-insurance systems should be assessed at an early stage, before these structural changes become more pronounced.
The Left has raised a different concern, warning that extensive AI use could increase workplace stress rather than simply improve efficiency. Donata Vogtschmidt, the party’s spokesperson for digital policy, has cited Harvard research associating intensive AI use with cognitive overload and higher levels of stress. She has also questioned whether the financial returns generated by major investments in the AI sector adequately reflect their costs, particularly as the technology’s energy consumption continues to grow.
Labor-market data reinforce concerns about the position of younger workers. An Ifo Institute survey found that half of German companies already using AI expect wages to decline over the next five years for employees with fewer than five years of professional experience. Among workers with at least five years of experience, roughly 40 percent of surveyed companies anticipate wage reductions, while only 9.7 percent expect wages to rise. Taken together, the results indicate that substantially more companies anticipate negative wage effects than positive ones, suggesting that the productivity gains expected from AI may not be distributed evenly among employees.
These developments are occurring even as young people’s participation in the labor force has increased. Data from the Institute for Employment Research show that youth labor-force participation has risen significantly since 2015 and is now at its highest level in decades, running counter to the widespread perception that Generation Z is insufficiently willing to work. At the same time, the transition into working life remains uncertain for many young people because temporary employment is still common. In 2025, 18.3 percent of employed people between the ages of 15 and 25 held fixed-term contracts, excluding apprenticeships.
AI reshapes jobs as entry-level workers face growing pressure
AI-related employment effects are also becoming visible, according to Goldman Sachs, although their overall impact remains relatively limited. Since the second half of 2022, industries with greater exposure to AI automation have recorded slower growth in job openings, with the pattern particularly evident in Germany, Australia and the United States. Employment growth in information and communications services, one of the sectors most exposed to AI, has slowed in most major developed economies. Employment levels, however, remain close to or above their long-term trends, underscoring the difference between slower growth and outright employment contraction.
The effects are more pronounced in certain industries. Employment in call centers, software publishing, business consulting and advertising has fallen significantly below historical trends. Call centers provide the clearest example: employment is estimated to be 39 percent below trend in the United States, 33 percent below trend in Canada and 27 percent below trend in Germany. Goldman Sachs’ analysis of more than 800 occupations also found that AI-related employment pressure is disproportionately affecting workers at the beginning of their careers. Across entire labor markets, the effect remains relatively modest, amounting to about 0.1 percentage point in France, Canada and the United States. For entry-level workers, however, the decline was substantially larger, exceeding 0.6 percentage point in Australia and 0.2 percentage point in the United States.
The financial industry illustrates a different aspect of the transformation. Although there has not yet been evidence of large-scale job losses, AI adoption has become firmly embedded in corporate strategy. KPMG’s 2026 study of generative AI in the German economy found that all 30 surveyed insurers had implemented an AI strategy, while 83 percent had established companywide policies. More than half reported increases in revenue, and 47 percent reported greater process automation. Improvements in data analysis and customer interaction were each reported by 40 percent of respondents, indicating that measurable business effects are already emerging even as broader implementation remains incomplete.
AI deployment in insurance is still concentrated largely in customer-facing functions, particularly sales and complaints management, even though insurers expect its greatest effects to occur elsewhere. Some 83 percent anticipate significant changes in claims and benefits processing, while 63 percent expect major effects on customer service and 40 percent on risk management. Sixty percent of respondents regard AI as a significant driver of operational transformation. Implementation, however, continues to present substantial challenges. More than half, or 53 percent, identify difficulties integrating AI into existing workflows and developing user-friendly applications, while half cite unresolved data-protection, security or compliance requirements as major barriers. Although all of the insurers surveyed consider themselves prepared for employees to use AI productively, only 57 percent currently provide companywide training programs, pointing to a gap between organizational readiness and practical workforce preparation.
Public institutions are also beginning to experience the effects of rapid AI adoption. Bavarian social courts are dealing with a sharp increase in filings, with court officials attributing part of the rise to AI-assisted submissions that frequently recommend unsuitable legal claims. The additional cases nevertheless require judicial processing, adding to an already heavy workload. The Bavarian social-court system is currently expected to face more than 38,000 substantive proceedings and about 7,000 expedited cases. First-instance filings increased by roughly 26 percent in the first half of 2026 compared with the same period a year earlier, with especially sharp increases in cases involving health insurance, unemployment benefits and basic income. Expedited proceedings more than doubled, while appellate filings rose by nearly 20 percent, further straining judicial resources.
Work is changed without triggering mass layoffs, PwC finds
The 2026 AI Jobs Barometer from PwC offers a broader international perspective on these labor-market changes. The study examines AI skills, wages, productivity and occupational change using more than one billion job advertisements from 27 countries, supplemented by corporate and labor-market data. Despite the particularly high level of AI exposure in the financial sector, the findings provide no evidence of widespread layoffs across the economy so far. Instead, the emerging pattern is one of significant occupational restructuring, with the consequences concentrated in particular areas rather than appearing as a uniform collapse in employment.
Real estate markets are undergoing similarly differentiated changes. A study by JLL, the Center for Real Estate and MIT’s Sloan School of Management concludes that AI is unlikely to reduce office demand consistently across markets. Its effects instead differ according to industry, market and asset class. AI can augment existing jobs without reducing headcount, eliminate selected occupations or create entirely new roles. More than one million AI-related jobs were created between 2023 and 2025, while AI was identified as the primary cause of roughly 5 percent of layoffs in 2025. The figures illustrate why employment losses alone provide an incomplete measure of the technology’s effect on demand for physical workspace.
This divergence is particularly visible in technology markets. In the United States, employment fell by 1.5 percent early in 2026, yet demand for office space in the technology sector continued to increase. San Francisco offers a notable example: despite being among U.S. markets with relatively high exposure to AI-related job displacement, nearly 30 percent of its office leases since 2025 have come from AI companies. The pattern suggests that long-term real estate performance may depend less on a market’s exposure to AI-related employment losses than on its capacity to adapt to changing industries, occupations and sources of demand.
Four broad market trends emerge from the analysis. Automation can reduce office demand where administrative teams become smaller; AI can increase demand for higher-quality, more collaborative workplaces by supporting skilled knowledge workers; industrial restructuring can redistribute employment geographically without reducing overall demand; and AI-native industries can create new demand for premium properties. Germany’s major cities occupy different positions within this changing landscape. Munich remains the country’s leading city for AI-related innovation and ranks first in Europe and 11th worldwide for AI research publications. Stuttgart benefits from significant research-and-development investment, while Berlin has produced 23 unicorns over the past five years, matching Toronto’s total. Across German cities, about $54 billion in venture capital has been invested during the same period, strengthening their prospects for AI-driven economic growth.
Up to seven gigafactories in the EU as Bosch plans humanoid robot production
The European Union is simultaneously working to build the infrastructure required to compete globally in AI. The European Commission has launched a tender for as many as seven AI gigafactories, seeking to expand computing capacity and strengthen Europe’s technological sovereignty. The initiative could receive up to 10 billion euros in European and national funding and is intended to mobilize at least 20 billion euros in additional private investment. The scale of the proposed program reflects the EU’s effort to establish infrastructure capable of supporting advanced AI development and deployment.
The planned facilities would combine advanced AI processors, cloud technologies, software platforms, high-speed networks and energy-efficient data centers. Startups, small and medium-sized businesses, industrial companies, researchers and public administrations would be given access to the infrastructure. In the first funding round, as many as four projects could receive grants of up to 500 million euros each. A second round could support up to three larger projects, with grants of as much as 1 billion euros each. To improve access to the high-performance hardware required for the facilities, the EU has also secured commitments from U.S. chipmakers AMD, Nvidia and Qualcomm.
The tender is scheduled to close on 12 November, with project selections expected in early 2027 and construction potentially beginning later that year. Depending on the timing of contract awards, the first facilities could begin operating in 2028, while later projects could extend into 2029. The European infrastructure push is taking place alongside another development in industrial automation, as AI increasingly moves from software applications into physical manufacturing.
In collaboration with London-based Humanoid, Bosch intends to begin series production of humanoid robots at its facility in Bühl, in southwestern Germany, in August 2027. The robots are being developed by the startup, while Bosch is expected to manufacture them under contract, initially producing several hundred units. Bosch is also considering supplying components such as sensors, motors and drives. The planned production represents the company’s entry into manufacturing this type of AI-controlled robot and adds a physical dimension to the broader automation trend.
Schaeffler is expected to be among the first customers and intends to use the robots in manufacturing. Bosch, Schaeffler and Humanoid already have business and investment relationships. Although the humanoid-robot market remains in its infancy, its potential applications extend from factories and logistics to health care and domestic assistance. Development is currently led primarily by companies in the United States and China, leaving the market at an early stage even as industrial applications begin to take shape.
Taken together, these developments suggest that AI is neither producing a uniform decline in employment nor generating evenly distributed productivity gains. Its effects depend substantially on occupation, seniority, industry, geography and institutional capacity. Some workers face greater wage or employment pressure, while other sectors are gaining investment, new roles and additional demand. For policymakers, the central challenge will be adapting taxation, social insurance, education and labor-market institutions to an economic system in which output may increasingly depend on capital and technology rather than traditional wage labor. For businesses and investors, meanwhile, the decisive issue is likely to be the ability to integrate AI at scale while reallocating workers, capital and physical infrastructure toward emerging sources of value.
