<p>This study explores how artificial intelligence (AI) is being used to support more sustainable production systems in chemical engineering. It combines bibliometric analysis with machine learning techniques to examine how research in this area has developed and where it is heading. Bibliometric analysis is used to map the global research landscape of AI-related sustainability studies, revealing key research themes, collaboration networks, and leading countries and institutions. Visual analyses generated using VOSviewer demonstrate the prominent role of AI-based analytical methods in chemical engineering applications such as industrial process optimization, environmental monitoring, and resource-efficient production. Alongside this, the study presents a targeted review of 113 peer-reviewed publications from a chemical engineering perspective, focusing on major application areas including sustainable manufacturing, wastewater treatment and membrane technologies, renewable energy systems, energy storage optimization, and sustainable supply chain management. Machine learning methods are also used to analyze changes over time and to provide an indication of future research directions. Overall, the findings show that AI is playing an increasingly important role in improving efficiency, flexibility, and sustainability across different stages of production. This work offers a structured overview of current developments and highlights opportunities for future research and practical implementation in sustainable chemical engineering systems.</p>