Artificial Intelligence (AI) has changed our lives. This also applies to the field of higher education. Teaching and working have changed permanently and will never be the same again as it was before ChatGPT was launched in November 2022. While the majority of recent research has focused on technical perspectives, this article addresses the possibility of AI entirely replacing the typical teaching at higher education institutions. It also highlights the perspective of lecturers. AI is significantly transforming the university landscape, affecting various aspects of lecturer’s roles and responsibilities. Positive aspects can be for example enhancement of teaching practices, administrative efficiency and their own professional development. However, also challenges appear, like ethical concerns and the adverse impact on student’s skill development. Hence, this raises the question: „ Does AI lead to the end of today’s Higher Education? Lecturers had to deal with these aspects and unanswered question. Moreover, the development goes on and on.

Our paper plans to provide an overview of which of these points are relevant for lecturers and how lecturers deal with them. Furthermore, we want to show how organizational aspects (university guidelines, training, provided software) influence the work of lecturer. It also demonstrates which support services for lecturers already exist. Additionally, it points out how lecturers see the beginning AI era. All the aspects mentioned above have an influence on the future of teaching in general, the enjoyment of teaching, motivation for working at the university, and as well as on overload and stress symptoms caused by AI. Of course, this inevitably raises the question which other variables (age, subject area, experience, etc.) potentially have an influence.

Sample and data collection process:
Sample of this paper are lecturers of different faculties at different universities in Germany. A questionnaire was used to collect the data. The advantage of a questionnaire strategy is that it provides standardized answers that make it simple to compile data. Because the topic of the paper is a very complex one, different quantitative (5point Likert scales, with an additional field “don’t know”) data were collected to triangulate findings. The collected data were analyzed with the objective of establishing links between AI and the changing nature of teaching and work in higher education. Furthermore, the data were analyzed by SPSS and MS Excel.

Measures:
In total, six different scales related to AI were established (new role of higher institutions instructors: from teacher to facilitator; enhancement of teaching practices and teaching efficiency; professional development; challenges and considerations; organizational aspects; joy of work). The used scales and items for the quantitative analysis were fully developed by the authors.

Keywords: Artificial Intelligence, AI, transformation of teaching, work satisfaction, digital transformation, competences for digital technologies.