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@article{184888,
        author = {SHAFEEN TAJ and Druthi S Prasad},
        title = {AI FAMILIARITY ACROSS GENDERS IN IT A COMPARATIVE PSYCHOLOGICAL STUDY},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {3638-3645},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184888},
        abstract = {The present study, AI Familiarity Across Gender in IT: A Comparative Psychological Study, investigates gender-based differences in familiarity, usage, satisfaction, and perceived fulfillment of future needs associated with Artificial Intelligence (AI) among IT professionals. AI has become a transformative technological force, increasingly deployed for automation, predictive analytics, process optimization, and decision-making within the IT sector (Dwivedi et al., 2021). Despite its rapid adoption, questions remain about whether gender influences AI engagement patterns and future expectations. A purposive sample of 30 IT professionals (15 male and 15 female) completed a structured questionnaire assessing their familiarity with AI applications, frequency of use, levels of satisfaction, and the extent to which they anticipated AI meeting future professional needs. Both descriptive statistics and inferential analyses, including one-way ANOVA, were employed to test for gender-related differences. Results revealed that although male professionals consistently reported slightly higher mean scores across all variables, the differences were not statistically significant. These finding challenges earlier assumptions of male dominance in technology adoption (Venkatesh & Morris, 2000) and points toward a narrowing gender gap, likely facilitated by equitable access to resources, inclusive workplace training, and digital skill development. The study contributes to ongoing scholarly discourse on digital adoption by highlighting the importance of inclusivity in AI integration. Furthermore, it offers practical implications for organizations, recommending larger and more diverse samples in future studies, as well as the inclusion of socio-demographic factors to better understand AI engagement in professional contexts.},
        keywords = {Artificial Intelligence, IT professionals, gender differences, technology adoption, ANOVA},
        month = {September},
        }