Last-mile delivery — from the distribution center to the customer’s door — accounts for 41–53% of total supply chain costs. AI attacks last-mile costs systematically.
AI cost reduction levers in last-mile delivery:
Route density: AI clusters deliveries by neighborhood to maximize stops per mile, reducing the cost per delivery.
Failed delivery reduction: AI predicts which deliveries are likely to have no one home based on historical data and schedules them at more likely times or offers alternatives (neighbor delivery, secure location).
Driver productivity: AI identifies the drivers who complete the most stops per hour and studies their habits to train other drivers.
Fuel optimization: Beyond route efficiency, AI monitors driving behavior (harsh braking, excessive idle time) that wastes fuel.
Returns consolidation: AI batches return pickups with delivery routes rather than running separate return trips.
Hub and spoke optimization: For larger operations, AI determines the optimal placement of micro-fulfillment hubs to reduce last-mile distances.
Demand prediction for staffing: AI forecasts delivery volume 7–14 days out, allowing optimal contractor/driver staffing without over- or under-staffing.
Cost per delivery tracking: AI tracks cost per delivery by route, zone, and driver — making profitability visible at the granular level that drives better decisions.
What is your current cost per delivery? Which cost component has grown fastest in the past year?