The complexity of engineering work and responsibility requires multifaceted preparation. Within this, communication skills play a prominent role, which, on the one hand, determines the efficiency of information transfer in dealing with complex systems, and, on the other hand, the success of dialogue with society and the representation of professional values and interests.

Recently, new problems have appeared and require answers, also in engineering education. Algorithms (software) are increasingly present in engineering work as "colleagues" rather than as tools. This results in the expansion of the space of communication processes, with H2M and M2M channels assuming an increasingly significant role in information transfer, in addition to the previously dominant H2H space. Several questions can be raised in this regard, e.g. how H2H communication changes when the parties involved work (individually or in a team) with an AI employee Previously, in a typical professional communication situation, the information had to be transferred about what each actor did within a project, they could detail their own work as needed now, what they did together with the AI employee has to be transferred since the details of the AI employee's activities are hidden.

In the literature on the content and methodological issues of engineering education, texts on the necessity of interdisciplinarity and multidisciplinarity occupy a decisive place, in which soft skills, including communication skills, play a prominent role.

The transdisciplinary education concept, which goes beyond interdisciplinarity and multidisciplinarity, is based on the active exchange of ideas among stakeholders, presenting real problem areas and decision-making situations in learning contexts.

A prerequisite for organizing transdisciplinary education, which also involves the latest digital technology, including generative AI, is that students have basic communication skills that they use consciously. To be prepared to support first-year students in being successful in it, it is necessary to examine their existing abilities, the extent to which they are aware of the expectations and challenges, and the extent to which they meet them.

The method of the investigation can be a questionnaire survey, an interview, or the creation of situations in which students must use their communication skills actively. In this talk, we present the results of a survey, during which we wanted to clarify the following: (i) whether students are aware of the requirements related to their future engineering work, (ii) whether they are aware of the extent to which they meet these, (ii) how they can mentally process their deficiencies, whether they have an idea of how these can be filled with help or self-training, (iii) how they judge the impact of the virtual environment surrounding them and the dominance of communication based on significantly simplified short text messages, (iv) what impact generative AI has on their interpersonal and professional communication.