Artificial intelligence is fundamentally changing the world of work, and its impact goes far beyond the introduction of new software or automated processes. It is becoming increasingly clear that the role of humans is shifting. As machines increasingly take on operational tasks, humans are moving into a position of management, evaluation, and control. Work is less about execution and more about classification, responsibility, and critical reflection on AI-supported results.
Current evaluations of global continuing education data make this change measurable. This is particularly evident in the Job Skills Report 2026 from the Coursera learning platform, which analyzes learning opportunities used worldwide. The report shows that generative AI is no longer a specialized discipline, but has developed into a cross-disciplinary skill. AI is now firmly established in areas such as data, IT, and product development. This trend is also reflected in Germany. Much of the most popular learning content is directly related to AI, especially data analysis and data-related skills.
What is striking is not only which skills are in demand, but also how their character is changing. Whereas previously the focus was on using individual AI tools, the focus is now shifting to application-oriented and evaluative skills. It is increasingly important to use AI systems productively, check their results, and understand their limitations. This increases the demand for analytical skills and a fundamental understanding of how these systems work.
Critical thinking is becoming particularly important. The demand for relevant learning opportunities has risen significantly within a short period of time. Companies are increasingly looking for employees who are not only able to accept AI results, but also to classify them, question them, and check their plausibility. At the same time, there is growing interest in so-called AI agents, i.e., systems that perform tasks largely independently. The more autonomously these systems operate, the more important human control becomes.
A central foundation of this development is data literacy. Topics such as data quality, data cleansing, and data ethics are seeing noticeable increases in demand. They illustrate that the benefits of AI depend significantly on the quality and responsible use of the underlying data. Without reliable data, even the most powerful models lose their significance. This is complemented by the growing importance of prompt engineering. The targeted formulation of inputs is evolving from a niche skill to a key qualification for the effective use of generative AI.
A change is also evident in the creative sector. Generative AI is now the most sought-after skill on the platform. Content creation in particular is growing strongly, indicating the widespread use of AI in communicative and creative activities. At the same time, there is increasing demand for more complex applications such as image analysis or multimodal prompts that combine text, images, and other data formats. These skills are also becoming increasingly relevant outside of traditional IT professions.
This results in a new skills profile for companies. The focus is shifting away from individual tools to a combination of technical understanding, critical evaluation, and responsible application. The decisive factor is not how quickly new AI systems are introduced, but how well employees are prepared for the changed division of labor between humans and machines. Individual pilot projects are not enough; rather, systematic skills development is required.
Conclusion
The transformation of the world of work in the age of AI clearly shows that the success of artificial intelligence depends less on the technology itself than on the people who use it. Not only technical skills are in demand, but above all analytical thinking, data competence, and the ability to critically evaluate AI results. Those who can assume this role of controlling and responsible authority will occupy a central position in the labor market in the coming years and help shape the productive use of AI in the long term.
