Introduction:
In recent decades, the rapid development of emerging technologies, particularly artificial intelligence (AI), has profoundly influenced higher education systems worldwide. The integration of AI tools into teaching and learning processes has generated a wide range of expectations and concerns. On the one hand, AI is considered a powerful strategic instrument capable of transforming instructional methods, enhancing learner autonomy, and expanding access to educational resources. On the other hand, it brings significant challenges including ethical dilemmas, infrastructural limitations, and potential risks of superficial learning or dependency on technology. In Iran, the discourse around AI in education is still evolving, and there is a need for empirical research that explores how future educators experience and perceive these technologies. Therefore, the present study aimed to conduct a strategic analysis of the lived experiences of student-teachers in applying AI in higher education, with an emphasis on understanding the paradoxical dualities, opportunities, and managerial challenges arising from this phenomenon.

Methodology:
This research employed a qualitative design with a phenomenological approach to capture the depth and complexity of participants’ experiences. The study population comprised 43 student-teachers from Farhangian University and Payame Noor University who participated in courses utilizing teaching strategies that encouraged the free use of AI-based applications and tools. Using purposive sampling, 18 participants were selected to ensure maximum diversity of experiences until thematic saturation was reached. Data were collected through in-depth semi-structured interviews, each lasting approximately 60–90 minutes. The interviews explored perceptions of benefits, challenges, and contradictions encountered when engaging with AI in educational contexts. Braun and Clarke’s thematic analysis framework guided the systematic coding and organization of data. To enhance trustworthiness, the study applied peer debriefing and member checking techniques.

Results and Discussion:
The analysis yielded a rich thematic structure organized into three primary domains: benefits, limitations, and paradoxical dualities. Benefits of AI Use: Participants emphasized that AI had transformative potential in higher education. Five main themes emerged in this domain: Transformation in Teaching: AI facilitated the personalization of content, adaptive learning pathways, and dynamic lesson planning, leading to more engaging and relevant instruction. Student Empowerment: Tools such as chatbots and intelligent tutoring systems increased learner autonomy and confidence by providing instant feedback and tailored support. Accessibility and Flexibility: AI expanded access to diverse educational resources beyond temporal and spatial constraints. Technological Learning Requirements: The integration of AI motivated students to improve their digital literacy and adapt to new learning paradigms. Social Interaction: Certain AI tools supported collaborative learning and enhanced peer engagement. Limitations of AI Use: Despite the perceived advantages, participants identified critical constraints. Six main themes were extracted: Health Problems: Prolonged use of AI tools led to eye strain, fatigue, and reduced physical activity. Access and Performance Barriers: Inadequate infrastructure, limited internet connectivity, and outdated hardware impeded effective utilization. Technical Challenges: Users faced difficulties in configuring and mastering complex AI applications. Educational Challenges: There were concerns that AI might encourage surface learning and reduce critical thinking. Ethical and Security Challenges: Participants worried about data privacy, algorithmic bias, and intellectual property issues. Future-Oriented Challenges: The uncertainty about AI’s long-term impacts on professional identity and employment prospects created anxiety. Paradoxical Dualities: One of the most significant findings was the identification of paradoxical dualities that underscored the multifaceted nature of AI in education: Content Orientation: While AI could generate neutral and objective materials, it sometimes produced biased or contextually irrelevant content. Learning Speed: Although AI accelerated information retrieval, it occasionally diminished deep reflection and critical analysis. Time Management: AI tools could optimize lesson planning but also led to time wastage due to technical disruptions. Classroom Focus: AI applications enhanced engagement for some students while distracting others. These contradictions align with previous studies, which emphasize that AI implementation requires careful regulation and ongoing evaluation.

Conclusion:
Overall, the study demonstrates that artificial intelligence holds substantial strategic potential for enhancing educational quality, personalizing learning experiences, and improving access to knowledge. However, realizing these benefits demands intelligent policymaking, robust ethical frameworks, and systematic investment in technological infrastructures. The findings underscore that educators and policymakers must approach AI integration with a balanced perspective, acknowledging both its transformative promise and its inherent risks. By addressing infrastructural gaps, clarifying ethical standards, and equipping teachers and students with necessary competencies, Iran’s higher education system can leverage AI in a way that is both innovative and responsible. This research contributes valuable insights for curriculum redesign and policy development aimed at fostering meaningful, equitable, and future-ready learning environments.