Artificial Intelligence in Sustainable Logistics: Opportunities for Carbon Reduction and Resource Optimization

Abstract The logistics sector is among the largest contributors to global greenhouse gas emissions on account of its heavy dependence on fossil-fuel-powered transportation, energy-intensive warehousing, and inefficient resource utilisation across supply chains. As governments, consumers, and investors increasingly demand environmentally responsible business practices, organisations are under mounting pressure to decarbonise their logistics operations without compromising service levels or cost competitiveness. Artificial Intelligence (AI) has emerged as a powerful enabler of this transition, offering data-driven tools that can simultaneously improve operational efficiency and environmental performance. This paper examines the role of AI in advancing sustainable logistics, with specific emphasis on opportunities for carbon emission reduction and resource optimisation. Drawing on secondary sources and recent scholarship, the study explores AI applications such as route and fleet optimisation, predictive maintenance, demand forecasting, warehouse automation, smart packaging, electric and autonomous vehicle integration, and carbon accounting systems. The paper further discusses illustrative industry examples, the barriers that hinder widespread AI adoption in logistics, and recommendations for practitioners and policymakers. The findings suggest that while AI offers substantial potential to reduce fuel consumption, emissions, and waste, its benefits are contingent upon data quality, infrastructure readiness, financial investment, and organisational willingness to change. The study concludes that a strategic, phased, and collaborative approach to AI adoption can help logistics firms achieve measurable progress toward carbon neutrality and resource efficiency goals.