This quantitative study, based on the Technology Acceptance Model (TAM), investigates AI adoption in educationwithout institutional guidance, introducing the concept of “unsolicited AI use.” Unlike previous studies onsolicited use, it examines how students and teachers independently engage with AI tools, raising concerns aboutequity, academic integrity, and pedagogical alignment. The unsolicited use of AI in education presents challenges,such as over-reliance, diminished critical thinking, and inequitable access, potentially undermining authenticlanguage acquisition. Data from 321 participants were analyzed using structural equation modeling (SEM) withTAM constructs: Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude (ATT), Behavioral Intention(BI), and Actual Usage (AU). This study was conducted across a number of Saudi universities, focusing onmultilingual English language classrooms in higher education settings. Results show that students link PEOUmore strongly to PU than teachers, with students viewing ATT as encouraging AI use (+0.14). Teachers, however,prioritize the AU-ATT relationship (+0.11). Fit indices (χ²/df = 6.76, RMSEA = 0.09, CFI = 0.87) indicatedTAM’s reasonable explanatory power. The findings have significant implications for English as a Foreign Languageinstruction, emphasizing the need for ethical and effective AI integration in language teaching contexts.The study highlights the need for AI competencies, equitable access, and contextualized approaches in multilingualeducation. Collaboration between teachers and policymakers is essential to ensure ethical and efficient AIuse. Future research should explore how AI-driven language learning impacts multilingual students’ educationaloutcomes over time.
Wael Alharbi (Fri,) studied this question.