Artificial Intelligence in Education and Research: Transforming Teaching and Learning in Economics

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in education and research, fundamentally reshaping teaching methodologies, learning experiences, and knowledge production in economics. This paper examines the role of AI in enhancing pedagogical practices, improving research efficiency, and redefining skill requirements in economics education. Drawing on recent empirical and theoretical literature, the study highlights key applications such as personalised learning, intelligent tutoring systems, data-driven research tools, and automated assessment. It also evaluates critical challenges including ethical concerns, academic integrity, digital inequality, and overreliance on AI systems. Empirically, the study utilised annual time series data from 2010 to 2024 and adopted the Autoregressive Distributed Lag (ARDL) model to analyse both short-run and long-run dynamics. Findings show that AI has a positive and statistically significant effect on learning outcomes in both the short run and long run. The paper concludes that while AI offers substantial opportunities for innovation in economics education and research, its successful integration requires strategic policy frameworks, ethical guidelines, and capacity building among educators and students.