Artificial Intelligence Adoption Among Community College Faculty: A Comparative Analysis of Rural and Urban Institutions

The rapid emergence of artificial intelligence (AI) has created new opportunities and challenges for higher education institutions. Community colleges, which serve diverse student populations and play a significant role in workforce development, must determine. The purpose of this quantitative study was to investigate differences in artificial intelligence (AI) adoption, usage patterns, and perceptions of importance among faculty at two rural community colleges and two urban community colleges in the United States. Specifically, the study investigated whether statistically significant differences existed in the perceived importance of AI and in the number of AI tools used by faculty across institutional contexts. In addition, the study identified the AI tools most frequently used by faculty in rural and urban community colleges. Data were collected using the Campbell University Artificial Intelligence Tool Usage Survey. A total of ninety faculty responses were collected from four community colleges, with eighty-six responses included finally. Descriptive statistics were used to summarize faculty perceptions and AI usage patterns. Independent samples t-tests were conducted to examine differences between rural and urban faculty in perceived importance of AI and the number of AI tools used. Frequency analyses were used to identify commonly used AI tools among rural and urban faculty. The results indicated that there were no statistically significant differences between rural and urban faculty in perceived importance of artificial intelligence. Descriptive analyses revealed that AI chatbots were the most frequently used AI tools among both rural and urban faculty, followed by writing assistants and instructional support tools. These findings suggest that artificial intelligence technologies are becoming increasingly present in faculty professional practices across community colleges. However, patterns of AI adoption appear broadly similar across rural and urban institutional contexts. The results highlight the importance of institutional support, professional development, and policy development to promote responsible and equitable integration of AI in community college teaching and learning environments.