This study examines the current usage patterns, perceptions, attitudes, and challenges related to the integration of AI technologies in higher education. Utilizing a structured survey complemented by semi-structured interviews, data was collected from 225 educators across various disciplines, ensuring a diverse representation. The descriptive statistics indicate a widespread use of AI tools, with high mean scores reflecting the frequent incorporation of AI in content delivery, assessment, and feedback. However, significant barriers such as lack of training and resources persist. The study's hypotheses were tested using Kruskal Wallis Test and regression analyses. The first hypothesis, that formal AI training significantly impacts AI integration, was validated, highlighting the crucial role of professional development. The second hypothesis, positing that positive perceptions of AI's potential benefits correlate with higher levels of AI integration, did not achieve statistical significance, suggesting that perceptions alone are insufficient to drive AI adoption. The findings underscore the necessity of comprehensive training programs and a holistic approach to addressing the multifaceted challenges of AI integration. While educators recognize AI's potential to enhance personalized learning and student engagement, the study reveals that systemic support and robust infrastructural frameworks are essential for effective implementation. This research contributes valuable insights into the factors influencing AI adoption in higher education and offers practical recommendations for educators, policymakers, and institutions striving to harness the full potential of AI technologies in teaching practices. By addressing these barriers, higher education can more effectively leverage AI to improve educational outcomes and student engagement.

Artificial Intelligence in Education, Higher Education Technology, Educator Perspectives AI Integration, Professional Development in AI