When global waves of layoffs become the harbinger of a fundamental economic transformation
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Published on: November 2, 2025 / Updated on: November 2, 2025 – Author: Konrad Wolfenstein
When global waves of layoffs become the harbinger of a fundamental economic transformation – Image: Xpert.Digital
Bigger than the Industrial Revolution? An invisible force is completely transforming our labor market.
The job revolution is here: Why your office job is now more at risk than you think
In the fall of 2025, a wave of mass layoffs sweeps across the global economy, affecting corporations like Amazon, UPS, Nestlé, and Procter & Gamble. But what at first glance appears to be a typical economic downturn reveals itself upon closer inspection as the harbinger of one of the most profound transformations in the world of work since industrialization. The driving force behind this transformation is not weakening demand, but rather the rapid and unstoppable implementation of artificial intelligence (AI) and automation in the core processes of these companies.
This new revolution differs fundamentally from previous upheavals: it no longer primarily affects factory workers or low-skilled labor, but is penetrating deep into offices and administrative floors that were previously considered secure. Analysts, administrators, and even executives are suddenly confronted with a technology that can perform their routine mental tasks more efficiently and cost-effectively. As companies make record investments in AI and thereby increase their profitability, a dramatic skills gap is emerging: millions of traditional jobs are disappearing, while new, highly complex roles are taking shape that demand a completely different set of skills.
This article analyzes the invisible revolution behind the layoff figures. It illuminates the true extent of the structural change, identifies which sectors and occupational groups are particularly affected, and examines the profound social consequences. It is a development that is shaking the foundations of our working society and confronting us all with the crucial question: How do we shape a future of work in which technology serves humanity, and not the other way around?
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Labor markets in transition – From the desk to the street? How AI is rewriting the rules of the labor market and who ultimately wins.
The worldwide announcements of massive job cuts in the fall of 2025 may not merely mark a temporary economic downturn, but rather the beginning of one of the most profound economic upheavals since industrialization. The figures are both impressive and alarming: In October 2025 alone, over 25,000 people lost their jobs at major corporations in the United States. The parcel service UPS has eliminated 48,000 positions since the beginning of the year. In Europe, more than 20,000 jobs are affected, with Nestlé making the largest single contribution at 16,000 job cuts. Amazon announced the elimination of up to 14,000 office jobs, although internally, the figure of up to 30,000 affected positions is being discussed.
What appears on the surface to be a reaction to economic weakness, upon closer analysis reveals itself as a symptom of a fundamental shift in the global economic architecture. Adam Sarhan, CEO of 50 Park Investments, puts it succinctly: If the economy were healthy, there wouldn't be such large-scale layoffs. But this diagnosis falls short. The current waves of layoffs differ qualitatively from those of previous economic cycles. They are not primarily affecting production workers or unskilled labor, but increasingly highly skilled office workers, administrative staff, and even executives.
The reasons for the job cuts vary considerably at first glance. At companies like Target and Nestlé, new executives want to restructure the organizations. Baby clothing manufacturer Carters is struggling with high import tariffs and is therefore cutting 15 percent of its office jobs. Procter & Gamble is eliminating 7,000 positions, equivalent to 15 percent of its administrative workforce, to reduce costs and simplify its organizational structure. However, closer examination reveals a common denominator: almost all of the affected companies are investing heavily in artificial intelligence and automation.
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The invisible revolution behind the numbers
The real transformation lies hidden behind the official justifications. According to a survey by the consulting firm KPMG, US companies are spending an average of $130 million on artificial intelligence, 14 percent more than at the beginning of the year. German CEOs plan to allocate more than 10 percent of their budgets to generative AI on average over the next twelve months; internationally, this figure is as high as 83 percent of companies. These investments are not abstract visions of the future, but concrete strategies for replacing human labor.
The focus on office and administrative jobs is particularly striking. These very jobs, considered secure middle-class employment for decades, are proving especially vulnerable to AI-driven automation. A study by the Federal Reserve Bank of Philadelphia shows that jobs requiring a college degree are more than three times as likely to be affected by AI as those without. The Institute for Employment Research predicts that 27 percent of companies in Germany expect job losses due to AI within the next five years. The manufacturing sector is particularly hard hit, with more than a third of companies planning for staff reductions.
Indeed's labor market expert, Allison Shrivastava, offers a cautious assessment: AI has the potential to transform the job market, but so far, no major impacts are visible. This assessment may be accurate for the moment, but it overlooks the speed of development. Between January and June 2025, 77,999 jobs in the technology sector were directly lost to AI, equating to 491 people per day. Thirty percent of US companies have already replaced workers with AI tools like ChatGPT.
The extent of the structural shift
The scale of the impending transformation is best grasped by looking at the forecasts of various research institutes. Goldman Sachs estimates that AI could automate the equivalent of 300 million full-time jobs. Around two-thirds of all jobs are already subject to some degree of AI automation. 27 percent of current working hours in Europe could be automated by 2030, while in the US the figure is as high as 30 percent.
The McKinsey Global Institute concludes that by 2030, around 30 percent of all work processes could be automated, affecting up to 800 million jobs worldwide. Physical labor and data processing jobs are particularly at risk. However, automation also creates new fields of activity. McKinsey predicts that overall demand for highly skilled profiles and jobs requiring social skills will increase, while the need for purely routine workers will decrease.
In Germany, the transformation is already manifesting itself in hard numbers. More than 10,000 industrial jobs are lost every month. In 2024 alone, German industry cut 68,000 jobs; by the first quarter of 2025, this figure had already reached 101,000 within a year. Since the pre-pandemic year of 2019, the number of industrial employees has shrunk by almost 250,000, a decline of 4.3 percent. The situation is particularly dramatic in the automotive sector, where approximately 45,400 to 51,500 jobs were lost within a single year – almost seven percent of the workforce.
The skills gap and its social consequences
The crucial challenge of the current transformation lies not in the number of jobs disappearing, but in the skills gap between job losses and new ones. While the World Economic Forum's Future of Jobs Report 2025 indicates that 170 million new jobs are expected to be created by 2030, while 92 million will be lost, resulting in a net gain of 78 million jobs, this seemingly positive balance masks a fundamental problem: 77 percent of new AI jobs require a master's degree.
The gap between disappearing and emerging jobs is thus far greater than during the historic automotive revolution. A data entry clerk cannot simply become an AI engineer without years of retraining. By 2030, 29 percent of the entire workforce will need to be retrained in their current roles, while 19 percent will have to embark on entirely new careers. Twenty million US workers will need to retrain for new careers or learn how to use AI within the next three years.
The skills gap remains the biggest obstacle to business transformation. Nearly 40 percent of the skills required in the workplace will change, and 63 percent of employers already cite this as their biggest hurdle. Two-thirds of companies are specifically seeking specialists with AI expertise, and 77 percent plan to launch comprehensive retraining programs.
The social impact of this skills gap is already being felt. The AI revolution is not affecting everyone equally. In the US workforce, 58.87 million women hold positions heavily exposed to AI automation, compared to 48.62 million men. Lower-paid workers are 14 times more likely to be affected than highly skilled professionals. Young workers are being hit particularly hard by the transformation. According to a Stanford study, employment of 22- to 25-year-olds in AI-intensive jobs has declined by six percent, while it has increased by nine percent in sectors with low AI use.
Deindustrialization or structural change
The debate surrounding current developments oscillates between two extremes: Is it a temporary economic downturn or a fundamental deindustrialization of Germany? The Institute for Macroeconomics and Business Cycle Research sees this development as a clear sign of deindustrialization. German industry is under immense pressure due to geopolitical shifts. Russia has ceased to be a reliable energy supplier, and both China and the USA are seeking to strengthen their own industries.
The figures are clearly alarming. In January 2025, 121,000 jobs were lost in German industry compared to the previous year. From June 2024 to June 2025, the number of unemployed in the industrial sector rose by 4.8 percent, or 69,000 people. The industrial sector's share of employment subject to social security contributions fell from 23 percent in June 2009 to just over 19 percent in June 2024. Small and medium-sized enterprises with fewer than 250 employees are particularly affected, either reducing staff or closing down entirely.
Jan Brorhilker of EY Germany issues a stark warning: German industrial companies are currently under immense pressure. Aggressive competitors, particularly from China, are driving down prices, key sales markets are weakening, and demand in Europe is stagnating at a low level. Employment trends are reacting with a delay to the weak sales performance, as companies are trying to avoid layoffs for as long as possible. However, the crisis in German industry has now become so entrenched that it is clear: significant downsizing is unavoidable.
The opposing view emphasizes the nature of structural change rather than deindustrialization. Based on the level of industrial value creation, no profound deindustrialization can yet be diagnosed in Germany. The structural change is triggered by the megatrends of digitalization, decarbonization, demographics, and deglobalization, which necessitate a restructuring of production processes. This process leads to the disappearance of established business models and the emergence of new production capacities. However, the outcome of this transformation, and especially the success of the new business models, remains uncertain.
For a successful transformation of the industrial sector, reliable economic policy decisions are needed, which must go hand in hand with a rapid improvement in location factors and thus international competitiveness. This includes a lower tax burden for companies, reduced bureaucracy and energy costs, the expansion of digital, energy and transport infrastructure, and an increase in the labor supply.
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Historical parallels and fundamental differences
To put the current transformation into perspective, it's worth looking at historical upheavals. The parallels to the transformation from horse-based agriculture to the rise of the automobile are striking. Between 1915 and 1960, the American horse population plummeted from 25 million to just 3 million animals, a decline of 88 percent. Entire professions vanished overnight: teamsters, farriers, carriage makers, and saddlers. While 1 to 2 million direct jobs and a maximum of 3 to 5 million including all indirect effects were lost in the horse industry, the automotive industry created a net increase of 6.9 million jobs between 1910 and 1950, representing 11 percent of the total US workforce in 1950.
Henry Ford's real achievement wasn't the invention of the automobile, which had existed since the 1880s. His revolution lay in the reinvention of work itself. When he put the first moving assembly line into operation at his Highland Park factory on October 7, 1913, he changed not only production but the very nature of human activity. The time required to assemble a Model T dropped from 12.5 hours to just 93 minutes, a 33-fold increase in productivity.
The crucial difference to the historical transformation, however, lies in the timeline. While the horse-to-car transformation unfolded over decades, offering a seamless transition, the AI revolution is taking place in years or even months. A carriage maker could become a car mechanic, a horse trader a car salesman. There was a parallel creation of new jobs and the disappearance of old ones. This temporal synchronicity is largely absent in the current transformation.
Another fundamental difference lies in the nature of the affected activities. Industrialization primarily replaced physical labor and simple manual skills. The AI revolution, on the other hand, is systematically intervening for the first time in intellectual tasks that were previously considered secure. Administrative staff, analysts, and even parts of management tasks are becoming automatable. A study by Horváth shows that in the IT & Digitalization sector, with an expected 16 percent increase in efficiency, one in six jobs could become obsolete due to the increased use of AI. This is followed by Sales & Marketing with 14 percent, Finance & Controlling with 13 percent, and HR with 12 percent expected efficiency gains.
Management tasks are increasingly being supported or even taken over by AI applications. This also results in potential savings of ten to twelve percent at the management level. Managers have hardly been affected by the efficiency potential of digitalization in the last two decades. The possibilities offered by AI are fundamentally changing this. The roles and activities of managers will change.
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AI is reshaping the job market: Winners, losers, solutions
The industry distribution of the transformation
The effects of AI-driven transformation are unevenly distributed across different economic sectors. Experts predict the most significant changes will affect office jobs in the administrative departments of companies and public institutions. More than half of all AI-related job changes in Germany fall into this category. Customer service and sales follow with 17 percent, while production jobs are affected by 16 percent.
Microsoft studies show that AI is gaining a foothold particularly in language- and analysis-intensive professions. Translators, historians, sales representatives, and radio presenters are among the professions with the highest AI penetration. At the same time, physical occupations such as nursing, skilled trades, and construction work remain largely unaffected. This distribution reverses traditional assumptions about job security: it is no longer academic training that protects against automation, but rather physical presence and social interaction.
In finance and accounting, companies are already experiencing a fundamental transformation. JPMorgan is automating routine banking functions, with 20 percent of analyst roles at risk by 2030. In product data management, fully automated workflows are emerging that handle PDF linking, CSV conversions, and product optimization without human intervention. Customer service centers that once employed 500 people are shrinking to 50 AI supervisory specialists.
More than 7.5 million data entry jobs will disappear by 2027. In customer service, 20 percent of jobs are at risk, and administrative support will shrink by over 600,000 positions. According to the World Economic Forum, graphic designers, payroll clerks, and postal workers are particularly likely to be affected by automation.
Interestingly, there are also sectors that benefit from the transformation. The World Economic Forum forecasts the strongest employment growth in absolute numbers by 2030 for frontline professions such as farmworkers, delivery drivers, caregivers, educators, and construction workers. The number of healthcare professions is expected to increase by 26 percent by 2035, while teaching and training professions will grow by 20 percent. Demographic change is driving demand in these areas.
The renewable energy sector offers particularly promising prospects. According to the German Federal Environment Agency, realized investments could create around 200,000 new jobs by 2030. Globally, the International Renewable Energy Agency forecasts an increase to 42 million jobs in the renewable energy sector by 2050. New professional fields are emerging at the intersection of technology and traditional industries: AI trainers, prompt engineers, AI ethics officers, and specialists in human-AI collaboration are examples of roles that did not exist just a few years ago.
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The efficiency trap and its economic implications
Paradoxically, the current waves of layoffs are often not a reflection of economic weakness, but rather a consequence of increased efficiency through the use of technology. Amazon CEO Andy Jassy stated that the 14,000 planned layoffs were due neither to cost reductions nor to the use of AI, but rather to the fact that those affected did not fit the company culture. This explanation seems contrived given that Amazon internally plans to automate up to 75 percent of its business operations and eliminate between 500,000 and 600,000 jobs in the coming years.
Despite announcing plans to cut 7,000 jobs, Procter & Gamble reported solid quarterly results with significantly increased profits. Net sales climbed three percent to $22.4 billion, while adjusted earnings per share surged an impressive 21 percent to $1.95. UPS also reported higher-than-expected quarterly profits despite a decline in package volumes, following the company's reduction of 48,000 jobs.
These examples illustrate a worrying trend: companies can increase their profitability through technology while simultaneously drastically reducing their workforce. The efficiency gains primarily flow into corporate profits and shareholder returns, not into higher wages or increased employment. McKinsey estimates the long-term potential of AI at $4.4 trillion in additional productivity growth. AI chatbots alone could generate $8 billion in annual business savings.
The economic implications of this development are ambivalent. On the one hand, productivity increases, which in principle enables gains in prosperity. McKinsey estimates that automation could boost annual global productivity growth by about 0.8 to 1.4 percentage points. On the other hand, profits are increasingly concentrated in the hands of capital owners, while labor incomes come under pressure. The risk of growing inequality is real if productivity gains are not translated into widespread prosperity.
Another problem is the concentration of AI development in a few large corporations. This could lead to monopolies and further weaken the bargaining power of employees. Data protection and security are becoming critical factors, as AI systems rely on enormous amounts of data.
Structural weaknesses of the German labor market
The current transformation is revealing deep-rooted structural problems in the German labor market that have been ignored or addressed with piecemeal solutions for decades. The mini-job system is an example of misguided labor market policy, the negative consequences of which are now clearly evident. Of the approximately 4.4 to 4.5 million people who work exclusively in a mini-job, representing about 11.4 percent of all employees, many have no prospect of regular, full-time employment subject to social security contributions.
The Institute for Employment Research has demonstrated that mini-jobs systematically displace regular employment. In small businesses with fewer than ten employees, an additional mini-job replaces, on average, half a position subject to social insurance contributions. Extrapolated figures show that mini-jobs have displaced approximately 500,000 jobs subject to social insurance contributions in small businesses alone. Model calculations by the Bertelsmann Foundation show that a reform abolishing mini-jobs could increase gross domestic product by €7.2 billion by 2030 and create 165,000 additional jobs.
The probability of losing a job is about twelve times higher for mini-jobbers than for employees subject to social insurance contributions. The high turnover rate of 63 percent compared to 29 percent for regular employees results in additional costs for recruitment and training. The coronavirus crisis demonstrated the vulnerability of this system particularly clearly: 870,000 mini-jobbers lost their jobs and fell directly into basic social security because they are not entitled to unemployment benefits.
The current situation in Germany is characterized by profound contradictions. On the one hand, industry is experiencing massive job losses, while on the other, many sectors are experiencing acute skilled labor shortages. Approximately 356,000 recipients of citizen's allowance worked exclusively in mini-jobs in July 2024, corresponding to approximately 43 percent of all employed citizen's allowance recipients. At the same time, thousands of positions in promising industries remain vacant due to a shortage of qualified specialists.
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Approaches to managing the transformation
Successfully managing the transformation requires coordinated efforts at all levels. For individuals, this means lifelong learning and a willingness to continuously develop their skills. 83 percent of experts agree: Demonstrating AI capabilities will provide current employees with greater job security than those who do not.
The most sought-after skills of the future are clearly defined. Analytical thinking tops the list, important to 69 percent of employers, followed by resilience and flexibility at 67 percent, and creative thinking. Technological competence, particularly in AI and cybersecurity, is becoming increasingly indispensable. Interestingly, human skills such as creativity, empathy, and flexibility remain crucial. A combination of technical and human skills is becoming ever more important in a rapidly changing job market.
Germany has taken important steps with the introduction of the citizen's income and the associated support for further training. Since July 1, 2023, recipients of citizen's income and those receiving unemployment benefit I receive an additional €150 per month if they participate in vocational training leading to a qualification. The education voucher covers up to 100 percent of the costs for retraining and further education, including examination fees, travel expenses, and, if necessary, childcare.
The Qualification Opportunities Act enables extensive funding for the vocational training and further education of employees by the Federal Employment Agency. Employees receive further training funding regardless of age, qualifications, and company size if their job can be replaced by technology, is otherwise threatened by structural change, or if they are seeking retraining in a shortage occupation.
Studies demonstrate the effectiveness of such measures. Participants in retraining programs have an employment rate almost 19 percentage points higher than similar non-participants. Comparing the professional status of individuals before and after unemployment, with one group participating in further training between the employment periods under consideration and the other not, those who participated in further training experienced career advancement more frequently and downward mobility less frequently than the comparison group.
Hybrid teams as a future model
The future lies not in the complete replacement of humans, but in hybrid models. AI takes over repetitive tasks while humans solve complex problems that require empathy, creativity, and critical thinking. This collaboration can increase productivity without eliminating the human element.
More and more companies are relying on hybrid teams where humans and AI work closely together. This allows repetitive tasks to be delegated to AI, while humans focus on strategic, creative, and interpersonal tasks. This collaboration leads to increased efficiency and greater employee satisfaction. In a hybrid team, AI doesn't replace human work, but rather enhances it. AI takes over monotonous, repetitive tasks and supports complex decision-making, allowing employees to concentrate on what matters most.
Successful navigation requires immediate retraining initiatives, strategies for human-AI collaboration, and coordinated public-private talent development programs. Companies that fundamentally realign their business models with AI and actively seek out specialists with specific AI skills are better positioned for the future.
Six aspects of successful transformation processes have emerged from empirical analyses. First, the necessity of the change must be clearly explained. Second, the strategy must be transparent. Third, existing needs should be taken into account. Fourth, opportunities for participation must be created. Fifth, investment in professional development is crucial. Sixth, a culture that learns from mistakes should be fostered.
Extensive employee participation in the changes is also a critical success factor. If management is the driving force behind the desired changes within the company and employees can effectively contribute to the transformation, both newly introduced work technologies and a diverse work environment will be used more intensively.
78 million jobs by 2030? Facts, risks and opportunities
The global waves of layoffs in 2025 are more than just a cyclical phenomenon. They mark the beginning of a fundamental transformation of the world of work, one that could surpass the industrial revolution of the 19th century in its depth and speed. The figures are clear: millions of jobs, particularly in office and administrative roles, will be replaced or fundamentally altered by AI-driven automation in the coming years.
However, contrary to what pessimistic forecasts suggest, this does not necessarily mean mass unemployment. Historical experience shows that while technological revolutions destroy existing jobs, they simultaneously create new fields of activity. The World Economic Forum forecasts a net increase of 78 million jobs by 2030. The crucial question is not whether there will be enough work, but whether the necessary retraining and qualification programs will be implemented in time to close the skills gap.
Germany faces particular challenges. Deindustrialization is progressing, structural weaknesses in the labor market, such as the mini-job system, hinder productive employment, and the speed of technological change overwhelms traditional adaptation mechanisms. At the same time, the country possesses considerable strengths: a highly skilled workforce, a functioning vocational training system, and increasingly better conditions for continuing education and retraining.
Successfully managing this transformation requires a paradigm shift: away from the fear of job loss and towards actively shaping new ways of working. Hybrid teams of humans and AI, combining technological efficiency with human creativity and empathy, point the way to a productive future. Massive investments in further training, the reform of hindering labor market structures, and a coordinated strategy between politics, business, and education are necessary to turn this crisis into an opportunity.
The course for the future of work is being set today. Whether the current waves of layoffs go down in history as harbingers of economic decline or as the birth pangs of a more productive and humane working world depends on the decisions made in the coming years. The transformation is inevitable, but it can be shaped.
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