Artificial Intelligence and Green Business Performance: Novel Insights From Saudi Arabia's Manufacturing Sector

ABSTRACT This study examines how artificial intelligence (AI), information and communication technologies (ICT), and sustainability innovation (SI) influence green business performance (GBP) in Saudi Arabia's manufacturing sector using panel data from 440 firms between 2017 and 2024. The research further evaluates the mediating role of sustainable supply chain (SSC) practices and the moderating effect of institutional quality (IQ) in shaping environmental performance. The study's core identification strategy relies on the System generalized method of moments (System GMM) estimator to address endogeneity, unobserved heterogeneity, and dynamic relationships within the panel data framework. The empirical results indicate that AI adoption, ICT investment, and sustainability innovation significantly improve green business performance among manufacturing firms. In addition, sustainable supply chain practices serve as a key mechanism through which digital technologies translate into improved environmental outcomes. The findings also show that stronger institutional quality, particularly regulatory effectiveness, governance standards, and transparency amplify the positive effects of technological adoption on sustainability performance. This study contributes to the growing literature on digital transformation and environmental sustainability in emerging economies by integrating technological capabilities, governance structures, and supply chain sustainability into a unified empirical framework. The results provide policy‐relevant insights for governments and industry stakeholders seeking to accelerate sustainable industrial development and support Saudi Arabia's Vision 2030 sustainability agenda.