Artificial Intelligence and Economic Growth in Malaysia: A Composite Index Approach Using PCA

Abstract

This study aims to examine the impact of artificial intelligence on economic growth in Malaysia using quarterly data over the period 2014–2024. To achieve this objective, a composite Artificial Intelligence Index (AI Index) is constructed using Principal Component Analysis (PCA) based on key technological indicators. The econometric analysis is conducted the Autoregressive Distributed Lag (ARDL) approach to investigate both short-run and long-run relationships between AI and economic growth, along with selected macroeconomic control variables.

The empirical results confirm the existence of a long-run equilibrium relationship among the variables. In the long run, the findings reveal that the AI Index, investment, and trade openness have positive and statistically significant effects on economic growth, while inflation has a negative impact. The results highlight the important role of technological advancement in enhancing economic performance. Based on these findings, the study recommends increasing investment in AI-related technologies, strengthening digital infrastructure, promoting high-technology exports, and maintaining macroeconomic stability to support sustainable economic growth.