This study investigates gender dynamics in the acceptance and integration of Artificial Intelligence (AI) tools among senior lecturers in foreign language (FL) instruction within Saudi universities. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) model, data was collected from 198 lecturers (95 males and 103 females) through a structured questionnaire, examining variables such as performance expectancy, effort expectancy, and facilitating conditions. Results indicate notable gender-based differences in AI adoption: male lecturers showed slightly higher positive attitudes towards AI, though female lecturers expressed greater confidence in AI’s effectiveness in enhancing student performance. Furthermore, a significant proportion of female lecturers reported greater ease and competence in using AI tools compared to their male counterparts, challenging traditional gender stereotypes in technology acceptance.
The study also reveals that female lecturers rely more on peer support and social influence in technology usage, with 88.34% finding AI more appealing when adopted by colleagues, compared to 46.31% of male lecturers. Both groups reported gaps in institutional support for AI integration, with only 32.64% of males and 37.86% of females perceiving adequate support from their universities. These findings underscore the importance of tailored training programs and resource distribution to address gender-specific needs and promote equitable AI integration in FL education. The study advocates for increased institutional support and inclusive technology training to foster a balanced adoption of AI tools in teaching practices across gender lines.