Abstract

The integration of Artificial Intelligence (AI) into supply chain systems is rapidly reshaping how organizations approach sustainability and meet Environmental, Social, and Governance (ESG) goals. This explores the intersection of AI technologies and sustainable supply chain practices, with a comparative focus on the United States and Nigeria two countries representing vastly different stages of economic development, digital maturity, and regulatory capacity. AI offers transformative potential across all three pillars of ESG: from monitoring carbon emissions and optimizing energy use, to enforcing labor standards and improving transparency in sourcing. However, the realization of these benefits depends heavily on national infrastructure, regulatory environments, and the maturity of ESG frameworks. In the United States, AI is increasingly leveraged by corporations to drive ESG performance, aided by supportive policies, advanced data systems, and a well-established culture of sustainability reporting. Tools such as predictive analytics, machine learning, and real-time tracking systems are used to measure environmental impact, improve ethical sourcing, and automate compliance reporting. Conversely, in Nigeria, AI adoption for ESG purposes remains limited, hindered by infrastructure deficits, low data availability, and weak regulatory enforcement. Despite these challenges, emerging initiatives in sectors like agriculture and logistics demonstrate growing interest in AI-driven sustainability. This highlights key contrasts between the two countries in AI readiness, ESG integration, and systemic barriers to adoption. It also identifies opportunities for strategic reforms in Nigeria, including capacity building, investment in data infrastructure, and stronger public-private collaboration. Meanwhile, the U.S. must address issues of AI ethics, workforce adaptation, and equitable access to technology. Ultimately, this underscores the role of AI as a critical enabler of sustainable supply chains and emphasizes the need for inclusive, context-sensitive strategies to advance ESG objectives globally.