Green Supply Chain Optimization: AI and IoT for Ethical Resource Management in Nigeria

Globally, supply chains operate under intense pressure to balance efficient, cost-effective performance with genuine environmental care. Customers, regulators, and investors expect clear insight into every step of the complex international web while demanding products delivered on time at competitive prices, even when markets fluctuate. This paper demonstrates how Nigerian firms can integrate artificial intelligence and Internet of Things (IoT) systems to utilise resources efficiently, reduce waste and emissions, uphold ethical standards throughout supply chain layers, and maintain operations nimble enough to meet rising sustainability expectations. The study employs mixed methods involving case studies from twelve multinational companies across the manufacturing, logistics, and retail sectors. Primary data collection includes structured interviews with supply chain managers, IoT sensor data from forty-five facilities, and blockchain transaction records spanning eighteen months across Nigeria. Secondary data encompasses sustainability reports, carbon footprint assessments, and operational performance metrics. By placing networked IoT sensors in factories, trucks, storage sites, and upstream suppliers, the article pairs real-time data with machine-learning routines that schedule preventive maintenance, forecast orders, and guide blockchain tracking, routing adjustments, and automated decisions balancing green goals with everyday performance. Data analysis utilizes regression modeling for performance correlations, time-series analysis for predictive maintenance patterns, and thematic analysis for qualitative interviews. Findings demonstrate that firms embracing AI-IoT eco-networks cut waste by 30-50%, trim carbon output by 20-35%, and maintain competitive costs. Results provide operations managers with tech-backed playbooks for responsible resource use without compromising profit motives, enabling operational excellence while meeting environmental and social responsibilities.