Predictions that artificial intelligence will either trigger mass unemployment or dramatically reduce the amount of work people perform have dominated public debate for years. According to sociologist Florian Butollo, neither outcome is likely. Instead, he argues that AI will fundamentally reshape how work is organized, generating new tasks and occupations while increasing expectations of productivity and quality. In an interview with Die Zeit, Butollo, a professor of sociology specializing in digital transformation and labor at Goethe University Frankfurt, contends that the future of work is likely to involve more employment rather than less, despite rapid advances in artificial intelligence.
The discussion comes at a time when businesses across industries are accelerating AI adoption while workers continue to question how the technology will affect their jobs. Recent examples have illustrated both the promise and the limitations of automation. Butollo points to reports that Ford recalled hundreds of experienced quality inspectors after artificial intelligence proved unable to perform their tasks as planned. For him, the episode reflects a broader pattern in which expectations surrounding AI frequently exceed its current capabilities.
According to Butollo, much of the public conversation is built around the assumption that artificial intelligence will replace human workers entirely. He argues that this overlooks a central characteristic of technological change: work itself evolves alongside new technologies. Rather than simply eliminating occupations, AI alters the nature of existing jobs while creating new ones that did not previously exist. In customer service, for example, automated systems increasingly handle routine interactions, yet employees are still required to develop, supervise, maintain, and improve the chatbots and AI systems that customers use.
While acknowledging that automation may reduce staffing requirements in certain roles, Butollo says the broader picture points in another direction. He argues that hundreds of thousands of people in Germany are already engaged in developing, implementing, and supporting AI technologies. Drawing comparisons with the spread of the internet, he says technological revolutions often become deeply integrated into everyday work without ultimately reducing the overall amount of labor society performs.
This argument forms the basis of his book, Das knappe Gut Arbeit (“The Scarce Resource of Work”), in which he contends that artificial intelligence is more likely to increase workloads than diminish them. He points to more than 150 years of technological automation, during which repeated predictions of mass unemployment failed to materialize. Instead, employment continued to expand even as machines transformed industries. Demographic change, he adds, is expected to reduce the number of available workers in coming decades, creating additional pressure on labor markets rather than widespread joblessness.
Butollo argues that previous forecasts often focused too narrowly on automation’s ability to eliminate existing tasks while overlooking the growing complexity of modern economies. Supply chains have become more intricate, products increasingly specialized, and divisions of labor more elaborate. Even the digital revolution, which many believed would eliminate routine work, instead generated large numbers of new jobs in logistics, delivery services, and information technology. Germany’s IT sector, he notes, has added hundreds of thousands of jobs during the past fifteen years despite existing primarily to automate processes and improve efficiency.
The same dynamic, he believes, extends across professional occupations. As technology becomes more capable, expectations surrounding professional output continue to rise. In academia, he observes, scholarly standards have changed dramatically over time. Earlier academic works often contained relatively few references, whereas contemporary research demands extensive documentation and citation. Similar developments can be found in software development, journalism, marketing, and other knowledge-intensive fields, where workers are expected to produce more sophisticated, faster, and increasingly polished results.
Although Butollo views artificial intelligence as a technological breakthrough unlike previous innovations, he argues that its significance lies in changing the relationship between humans and machines rather than replacing people outright. AI can generate large portions of computer code or assist with complex tasks, yet human workers continue to perform critical functions involving judgment, oversight, collaboration, and adaptation. He recalls conversations with software developers who report that AI now generates most of their code while leaving them with workloads as demanding as ever.
Current challenges in Germany’s labor market, he argues, should not be interpreted primarily as consequences of artificial intelligence. Layoffs in sectors such as automotive manufacturing reflect broader economic pressures affecting Germany’s growth model rather than AI-driven automation alone. The automotive industry itself illustrates how technological innovation can coexist with sustained employment. Even as production lines became increasingly automated, growing vehicle complexity and faster product cycles created demand for engineers, software developers, and other specialized professionals.
Butollo nevertheless recognizes that artificial intelligence will displace some occupations. Creative industries, including illustration, translation, and voice acting, have already expressed concerns about declining demand as AI-generated content expands. Rather than viewing those developments as inevitable, he argues that societies will have to determine where automation is acceptable and where human-produced work should remain the preferred standard. He also suggests that growing volumes of AI-generated material may increase appreciation for work produced directly by people.
Predictions that technology would dramatically reduce working hours are not new. Economist John Maynard Keynes famously envisioned a future in which people would work only fifteen hours per week. Butollo notes that nearly a century after that prediction, no such transformation has occurred. While he does not rule out more profound changes in the distant future, he argues that current AI systems remain fundamentally limited. They generate probable responses rather than genuine understanding, lack consciousness, and cannot independently comprehend the world they describe.
He also questions the widespread assumption that AI is already delivering dramatic productivity gains. Individual tasks, such as preparing presentations or producing graphics, may take less time than before. Yet those efficiencies are often offset by rising expectations from employers and clients, who increasingly assume that AI allows for faster, more sophisticated output. Referring to research examining AI use in real workplaces, Butollo argues that employment consists of dynamic, interconnected activities that cannot simply be divided into isolated tasks suitable for automation.
The sociologist also points to sectors where labor demand is expected to continue rising regardless of technological progress. Healthcare, elder care, childcare, and social services face growing staffing shortages as populations age. Expanding workforce participation in other sectors creates additional demand for care services, making these occupations increasingly central to future labor markets. According to Butollo, improvements in working conditions and public investment have already helped attract more employees into nursing, demonstrating that policy decisions can influence labor supply in critical sectors.
Beyond the immediate debate over artificial intelligence, Butollo argues that societies face broader decisions about how technological innovation should be directed. He suggests that governments should invest more heavily in research addressing public challenges such as infrastructure, education, energy, climate change, and healthcare rather than relying primarily on market-driven innovation aimed at commercial consumer products. As labor shortages intensify and artificial intelligence becomes more deeply integrated into workplaces, he contends that determining which forms of work deserve priority will become an increasingly important question for policymakers, employers, and workers alike.
