This chapter analyzes the role of artificial intelligence (AI) in academic work and situates it within the historical development of digital technologies. It describes how AI, and in particular large language models, are increasingly taking on tasks in research and teaching, such as text analysis, structuring literature, or selecting methods. These systems enable the automation of repetitive work steps and create space for conceptual thinking. At the same time, the chapter identifies key challenges, such as lack of transparency, potential biases, and the risk of homogenizing scientific forms of expression. It emphasizes the importance of scientific integrity, methodological diligence, and critical reflection when dealing with AI-supported tools. Responsibility for scientific content remains entirely with the researchers. The chapter also outlines future application scenarios and derives new competency requirements, as the confident use of AI is becoming a key qualification in the academic context.