The rise of AI tools, such as ChatGPT, has brought significant changes to higher education, as these tools are not only assistants as previous educational technologies but also actively participate in content creation (Denny et al., 2023). These technologies have introduced both opportunities to enhance instructional design, assessment, and student engagement, as well as challenges related to academic integrity, ethical use, and professional identity (Rasul et al., 2023; Yadav, 2024). Research shows that generative AI can facilitate instructional design, feedback, and self-directed learning (Roe & Perkins, 2025). At the same time, concerns have been raised about scientific authenticity, overreliance on students, and changes in academic learning (Khatri & Karki, 2023). As a result, new questions have arisen about their role in teaching and learning, the changing nature of scholarly work, and the evolving responsibilities of faculty members in higher education.

One of these questions concerns changes in how university professors operate as the primary agents of education in higher education. As pedagogical models, ethical debates, and technologies continue to develop in this space, university teachers’ experiences of teaching with GenAI have yet to be explored in detail (Ellis, Han, & Cook, 2025).  Tillmans et. Al. (2025) reviewed the state of GenAI in higher education, aiming to inform curriculum design and further developments within digital education. Findings revealed themes like mentorship, personalized learning, creativity, emotional intelligence, and higher-order thinking, highlighting the persistent need to align human-centred educational practices with the capabilities of GenAI technologies.

Technological Pedagogical Content Knowledge (TPACK) has, for the past two decades, been the defining framework for teachers' knowledge of integrating intelligent and intentional technology into teaching (Mishra, Warr, & Islam, 2023). The TPACK framework provides a valuable lens for examining how faculty integrate GenAI tools, such as ChatGPT, into teaching. Mishra et al. (2023) argue that GenAI fundamentally reshapes the intersection of content, pedagogical, and technological knowledge within this framework, thereby requiring educators to develop new strategies to blend these domains effectively. Faculty must not only understand the subject matter (CK) and appropriate pedagogical methods (PK) but also navigate the unique affordances and limitations of GenAI (TK). Chiu (2025) also emphasizes that the TPAC framework should be reconsidered, given that artificial intelligence is a product of specific technologies.

Experiences reported by instructors often reveal tensions, such as reconciling traditional teaching norms with AI-enhanced practices, managing academic integrity, and adapting assessments. Chan et. Al. (2025) examines how generative AI is used in teaching, learning, assessment, and research at Southeast Asian universities. Using hermeneutic phenomenology, the lived experiences of university teachers yielded three main themes: learning anew, disequilibrium and lack of rootedness, andambiguity about new norms and practices. Teachers in that study reported that GenAI both enhanced efficiency and disrupted established habits, creating personal, fragmented, and evolving ways of working. Many experienced tension between traditional academic norms and the transformative potential of GenAI, raising concerns about integrity and professional roles. Participants highlighted the urgent need for clear AI guidelines, AI literacy, and targeted training to promote.

Nevertheless, few studies have examined faculty members' perceptions of the use of generative artificial intelligence in teaching and learning. This is because this technology is under development, and therefore, such research seems necessary. This study examines faculty members’ experiences with generative AI in Iranian higher education, focusing on how these technologies influence teaching practices, professional roles, and perceptions of educational responsibility and may result in a reconceptualization of TPACK. Therefore, the main question this study seeks to investigate is: What is TPACK in the GenAI Era, as perceived by university faculty members’ lived experiences? 

The present study adopted a phenomenological research approach to investigate participants' lived experiences. The participants consisted of faculty members at Bu-Ali Sina University in Hamedan, Iran. They were all selected from the Humanities department. Twelve participants were selected based on theoretical saturation. Data were collected through semi-structured interviews, each lasting approximately one hour. All interviews were audio-recorded and transcribed verbatim. The interview transcripts were analyzed using coding and categorization procedures. The trustworthiness of the findings was enhanced through iterative analysis and member checking.

The study's findings showed that faculty members identified opportunities to improve access to educational resources, support customized learning, and increase efficiency in preparing course materials. They also raised challenges, including ethical concerns and scientific credibility, a lack of technical and educational readiness, and the complexity of managing fraud. In addition, their professional perceptions of their role indicate a shift from the traditional knowledge-transfer role to a guidance role. They also believe that it is not just their role that has changed, but also the nature of TPACK. They believed that, since GenAI could choose and even create content and make it pedagogical, they could move beyond the content they presented in the traditional classroom. This move is not only about the amount of content but also about the depth. They believe that the purpose of higher education may change in the future, so university professors should prepare students to face these conditions rather than emphasizing content. They also explained changes in the pedagogical process, noting that the most significant change is in the area of learning assessment. The findings indicate that although generative AI can provide new possibilities for optimizing educational activities, its effective adoption requires teacher training programs, clear ethical frameworks, and a rethinking of lesson design. This article contributes to a better understanding of how faculty interact with generative AI and provides a clear path for future research in this emerging field.

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