Determinants of AI adoption and its impact on organizational performance: A quantitative analysis in the digital economy

Abstract

The rapid advancement of artificial intelligence (AI) technologies has fundamentally transformed organizational operations in the digital economy, yet adoption rates remain inconsistent across industries and geographical contexts. This quantitative study examines the determinants of AI adoption and its subsequent impact on organizational performance within Malaysian organizations operating in the digital economy. Utilizing a cross-sectional survey design, data were collected from 384 organizations across multiple sectors in Malaysia through stratified random sampling. The research employs multiple regression analysis and hierarchical regression modelling using SPSS to examine relationships between technological, organizational, and environmental factors and AI adoption decisions, as well as the mediating effect of AI adoption on organizational performance. Results indicate that relative advantage (β = 0.342, p < 0.001), top management support (β = 0.287, p < 0.001), organizational readiness (β = 0.256, p < 0.01), and competitive pressure (β = 0.219, p < 0.01) significantly predict AI adoption. Furthermore, AI adoption demonstrates a significant positive impact on organizational performance (β = 0.468, p < 0.001), explaining 52.3% of the variance in performance outcomes. The findings contribute to the technology adoption literature by validating the Technology-Organization-Environment (TOE) framework within the Malaysian digital economy context and provide practical implications for organizational leaders seeking to leverage AI technologies for competitive advantage. This study addresses critical gaps in understanding AI adoption patterns in developing economies and offers evidence-based insights for policymakers and practitioners navigating digital transformation initiatives.