This study investigates differences in artificial intelligence (AI) literacy and adoption between engineering students and faculty in a Middle Eastern higher-education institution. Parallel surveys were administered to undergraduate engineering students (N = 73) and faculty members (N = 20), each rating their familiarity with 20 AI tools covering learning, coding, productivity, and engineering applications. An AI Literacy Index was computed by assigning numerical values to familiarity ratings (A = 2, B = 1, C = 0) and normalizing the total to a 0–1 scale. Results from Welch’s t-test indicated that students demonstrated significantly higher literacy than faculty (0.454 vs. 0.356, p ≈ 0.042). Students also reported strong AI adoption for academic tasks (71.2%) and high perceived learning benefits (83.6%). Conversely, faculty expressed substantial concern about student over-reliance on AI (90%) while indicating readiness for professional development through AI training workshops (75%) and reporting assessment redesign efforts (75%). Overall, the findings highlight a meaningful literacy and perception gap with implications for engineering pedagogy, curriculum development, and assessment practices. Recommendations are provided to support the alignment of student and faculty AI competencies within engineering programs.