Centralized cloud AI increases energy consumption and carbon emissions due to massive data transfer and processing needs. Moving to an edge-first AI architecture allows supply chains to process data locally on sensors and robots, reducing the load on power-hungry data centers. Edge AI improves sustainability by filtering data at the source and optimizing logistics in real time. This approach lowers network traffic and energy use while maintaining the efficiency gains of AI-driven demand forecasting and predictive maintenance.
