Regardless of the area of application, genAI has opened up numerous possibilities in recent years. In addition to technical development issues, the key to its successful use lies in personal acceptance. According to the general approach to this technology, it cannot be understood without “humanware.” Outcomes are shaped by individual perceptions, attitudes, skills, emotions, and behavioral responses, emphasizing the critical role of the human dimension in contemporary digital ecosystems.

The experiences of recent years have revealed both positive and negative aspects. Fear, uncertainty, and AI hallucinations raise numerous questions. Alongside those who embrace technology, there is a growing camp of those who reject it or remain skeptical. It is similar to the emergence of JOMO (joy of missing out) alongside FOMO (fear of missing out). Both sides offer valuable lessons learned, p erhaps they cannot even be understood without each other.

The special track aims to explore the personal, behavioral, psychological, and knowledge-related factors that influence adoption, effective use, rejection, or discontinuance of intelligent technologies. Theoretical research findings, model-building initiatives, and empirical results that help us understand the personal factors influencing technology adoption and related reservations. These findings will assist technology developers, strategists, and educational institutions in devising targeted measures. Legal, management, or technical management issues may all be of interest, but a systems-oriented approach is important, that is, articulating implications that demonstrate the utilization of the technology at the ecosystem level as well.

Submitted papers may address issues generally related to the use of generative AI or specific applications built upon it, including automation, system building through which they can contribute to the “ecology of knowledge.” Additionally, impact analysis on digital well-being, digital trust, digital competencies and technostress can be considered.

From a methodological perspective, in addition to literature reviews, case studies, structural and regression analyses, and expert assessments, we also welcome innovative solutions.