Are College Students Ready to Learn AI?—A Readiness Perspective

ABSTRACT As artificial intelligence (AI) becomes increasingly integrated into education and the modern workforce, understanding what drives students to learn AI is essential. This study investigates the factors influencing college students’ intention to learn AI, focusing on the roles of AI learning readiness (ALR), career readiness, AI literacy (AIL), intrinsic motivation, and extrinsic motivation. Data were collected from 313 Vietnamese college students and analyzed using partial least squares structural equation modeling. The results show that ALR, career readiness, and AIL significantly enhance both intrinsic and extrinsic learning motivation. In turn, both types of motivation positively influence AI learning intention (ALI). AIL also directly predicts ALI and exerts the strongest total effect among all predictors. The model demonstrates high explanatory power, with R 2 values exceeding 0.84 for all endogenous constructs. These findings contribute to the growing body of AI education research by highlighting the importance of readiness and literacy in shaping learning behavior. Practical implications extend beyond curriculum design to include career development initiatives and policy strategies that equip students with the competence, preparedness, and sustained motivation required to thrive in an AI‐driven labor market.