The Influence of Achievement Motivation on Consumer Adoption of Artificial Intelligence Applications: An Empirical Study

Abstract

Artificial Intelligence (AI) applications have become increasingly integrated into consumers' personal, educational, and professional activities, necessitating a deeper understanding of the factors influencing their adoption. While existing research on AI adoption has predominantly emphasized technological determinants, comparatively limited attention has been devoted to the role of psychological factors. Grounded in McClelland's Need for Achievement Theory and supported by technology adoption literature, the present study examined the influence of achievement motivation on consumer adoption of Artificial Intelligence applications. A quantitative, descriptive-correlational research design was employed, and data were collected from 450 consumers using a structured questionnaire. The collected data were analyzed using descriptive statistics, Pearson's Product-Moment Correlation, and Simple Linear Regression analysis using Jamovi Statistical Software Version 2.7.12. The findings revealed a strong positive and statistically significant relationship between achievement motivation and consumer adoption of AI applications (r = .796, p < .001). Furthermore, achievement motivation significantly predicted AI adoption behaviour (β = .796, t = 27.866, p < .001), explaining 63.4% of the variance in consumer adoption of Artificial Intelligence applications (R² = .634). The findings highlight the importance of psychological determinants in understanding consumer adoption behaviour and contribute to the existing literature by extending traditional technology adoption research beyond technological factors.