AI Economics for Logistics & Supply Chain
Logistics technology operates at the intersection of real-time systems, IoT scale, and AI forecasting. Each dimension creates distinct engineering economics.
Real-Time System Debt
Tracking operations in real-time creates high-throughput, low-latency requirements that drive cloud infrastructure costs.
IoT Scale
GPS trackers and RFID readers generate billions of data points. IoT infrastructure debt grows as devices age and scale.
AI Forecasting Economics
Demand forecasting and route optimization are AI-intensive. Inference costs scale directly with SKU and route complexity.
Integration Complexity
ERP systems, WMS, TMS, carrier APIs, and customs platforms create layered integration debt. Each new partner adds API maintenance cost forever.
How I Help Logistics Companies
- → Model real-time system infrastructure costs as tracking volume scales
- → Calculate AI forecasting COGS per SKU/route to optimize model economics
- → Quantify integration debt from carrier/ERP/WMS API maintenance
Need a sector-specific audit?
I run R&D capital audits tailored to your industry's cost structures, compliance requirements, and scaling patterns.
Richard Ewing — AI Economist & Capital Auditor