Generative Artificial Intelligence (GAI) is increasingly adopted in academic teaching and research environment because of numerous benefits such as data analysis, personalized learning, research design, focused tutoring. However, there are several concerns regarding academic integrity, research ethics and biases while adopting GAI in teaching and research. The primary objective of this study is to explore faculty perceptions of GAI in academia through insights from data analysis from the faculty members at the School of Engineering, Bowling Green State University (BGSU) along with the literature-based analysis. Faculty feedback was collected after conducting a seminar on AI in teaching and a presentation on AI in research. In teaching, findings show that most of the faculty agree about the potential of GAI in reducing their workload, skill growth, saving time, and personalized learning. They also recognized AI’s potential in automating research processes, application in different fields, innovation in research as well as strong motivation to apply AI in the academic environment. Furthermore, the analysis of literature provides valuable insights into the ongoing discussions on AI adoption, ethical needs, faculty training and the importance of clear policies. The mixed method approach provides valuable information about the critical need of the integration of AI in academia.