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Complete

Abstract

While AI is transforming professional practice and education, evidence indicates a persistent gender gap in AI use. Integrating gender theory with the Unified Theory of Acceptance and Use of Technology (UTAUT), we examine gender differences in predictors of AI use and performance outcomes in a global sample of business students. Results show that women report lower AI use than men. Performance expectancy predicts use for both genders but more strongly for men. Women’s use is additionally shaped by effort expectancy and negatively affected by social influence. Higher AI use was associated with increased performance among men but not women, indicating a gender difference in the relationship between AI use and performance. Targeted interventions that build AI literacy, self-efficacy, and emphasize voluntary engagement may promote more equitable AI adoption and performance outcomes.

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1685

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Aug 15th, 12:00 AM

AI for All? Understanding Adoption and Performance Across Genders

While AI is transforming professional practice and education, evidence indicates a persistent gender gap in AI use. Integrating gender theory with the Unified Theory of Acceptance and Use of Technology (UTAUT), we examine gender differences in predictors of AI use and performance outcomes in a global sample of business students. Results show that women report lower AI use than men. Performance expectancy predicts use for both genders but more strongly for men. Women’s use is additionally shaped by effort expectancy and negatively affected by social influence. Higher AI use was associated with increased performance among men but not women, indicating a gender difference in the relationship between AI use and performance. Targeted interventions that build AI literacy, self-efficacy, and emphasize voluntary engagement may promote more equitable AI adoption and performance outcomes.

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