Systematic Review Of AI-Improved Strategies For Sustainable Logistics: Evaluating Supply Chain Resilience In South Africa’s Environmental Context
This investigation examines the potential of Artificial Intelligence (AI)-enhanced strategies to enhance the resilience of supply chains and logistics in South Africa’s challenging environment. The global disruptions, particularly those emphasised by the COVID-19 pandemic, have rendered the establishment of resilient and sustainable logistics systems an urgent priority. This study examines the impact of AI on improving efficiency, sustainability, and resilience in the logistics sector of South Africa’s supply chain practices. This study uses a systematic review approach that is based on the PRISMA framework. A thorough literature review was performed, concentrating on the convergence of artificial intelligence, sustainable logistics, and South Africa’s environmental issues. Thematic analysis was conducted using Atlas-ti software to identify and organize key themes related to AI applications in logistics and supply chain management. Studies were selected based on predefined criteria. The results highlight the critical role of AI technologies, including machine learning, predictive analytics, and big data analytics, in the advancement of sustainable logistics. AI applications improve transportation efficiency, optimize inventory management, diminish carbon emissions, and augment supply chain transparency. The emergence of AI-driven solutions and GSCM frameworks, which are in alignment with sustainable practices and improve operational resilience, is a noteworthy trend. The synthesis indicates an increasing dependence on AI and big data analytics to improve supply chain capabilities and augment adaptability to environmental disruptions. The study concludes that AI-improved strategies provide significant advantages in the promotion of sustainable logistics and the improvement of resilience in supply chain operations. The implementation of AI solutions improves operational efficiency and aligns logistics practices with environmental sustainability objectives. The findings of this investigation offer valuable advice to academics, policymakers, and industry professionals who are striving to leverage AI for sustainable supply chain management in South Africa.
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