This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure the motivation levels of individuals using artificial intelligence (AI) applications. The QAIUM is grounded in the Expectancy-Value Theory, which posits that motivation consists of two fundamental dimensions: expectancy and task value. The task value dimension is further divided into four subdimensions: attainment, utility, intrinsic interest, and cost. The study involved 1068 university students from various faculties in Turkey and evaluated the QAIUM for its factorial structure, reliability, discriminatory capacity, and correlation with the General Attitudes to Artificial Intelligence Scale (GAAIS). The results demonstrate that the QAIUM aligns with the Eccles and Wigfield motivation model, exhibits good reliability, and has a significant correlation with the GAAIS, confirming its validation and reliability. The study contributes to the understanding of motivational factors that govern AI application use in academic instruction and intervention.This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure the motivation levels of individuals using artificial intelligence (AI) applications. The QAIUM is grounded in the Expectancy-Value Theory, which posits that motivation consists of two fundamental dimensions: expectancy and task value. The task value dimension is further divided into four subdimensions: attainment, utility, intrinsic interest, and cost. The study involved 1068 university students from various faculties in Turkey and evaluated the QAIUM for its factorial structure, reliability, discriminatory capacity, and correlation with the General Attitudes to Artificial Intelligence Scale (GAAIS). The results demonstrate that the QAIUM aligns with the Eccles and Wigfield motivation model, exhibits good reliability, and has a significant correlation with the GAAIS, confirming its validation and reliability. The study contributes to the understanding of motivational factors that govern AI application use in academic instruction and intervention.