AI-Personalised Learning in Higher Education: A Study on Learning Outcomes and Motivation among University Students

Artificial Intelligence (AI) has emerged as a transformative force in reshaping educational practices, particularly through personalized learning systems that adapt to individual student needs. This study investigates the impact of AI-personalized learning platforms on university students’ academic outcomes and motivational levels, focusing on business and management faculties across selected Southeast Asian institutions. Drawing on Self-Determination Theory and the Technology Acceptance Model, the research employs a mixed-methods approach combining survey data, learning analytics, and academic performance records. Results indicate that AI-driven personalization significantly enhances intrinsic motivation, learning satisfaction, and academic performance. However, digital literacy and prior exposure to adaptive technologies moderate these effects. The findings underscore the potential of AI to bridge learning gaps and support scalable, inclusive, and efficient education models in higher education, particularly in the post-pandemic digital economy. Implications for edtech adoption, policy development, and curriculum design in business education are discussed.