Artificial intelligence (AI) techniques, based on machine learning (ML) and deep learning (DL), are integrated across various phases of the lignocellulosic bioethanol supply chain, including pretreatment, hydrolysis, and fermentation. These incorporations enhance the predictive ability of process accuracy, process optimization, and economic viability, thereby boosting the commercialization of sustainable 2G bioethanol production systems. This book chapter presents an extensive review of the global bioethanol market, with a particular focus on lignocellulosic biomass. The basic concept of AI and its various approaches, utilizing ML and DL algorithms, are discussed for the 2G bioethanol process intensification. Additionally, a bibliometric study systematically evaluated research publications on AI applications in lignocellulosic biomass over the past decade. In addition, challenges, opportunities, and future directions for integrating AI into 2G-bioethanol production are briefly discussed. Therefore, by combining advanced AI tools into LCB-based biorefinery systems, a continuous 2G bioethanol production system can be developed despite seasonal variability in feedstocks and contribute to a sustainable energy future.