AI Should Earn Authority Gradually, Not All at Once

Burq, a last-mile delivery orchestration platform, has published a new deployment framework called 'Earned Autonomy' that challenges how AI vendors typically approach implementation in supply chain operations. Rather than requesting full operational authority on day one, Burq argues AI should begin with no authority and earn trust gradually through live order performance, with human approval required at each escalation step. The framework divides operations into segments, such as delivery mode (parcel, LTL, gig, drone), and implements a four-rung authority ladder: Manual (AI observes only), Shadow (AI logs silent recommendations), Review (AI proposes and human approves), and Autonomous (AI acts independently within segment rules).

Each segment earns authority independently based on retailer-defined performance thresholds. Promotions are automatic only when targets are met; demotions happen immediately if AI breaches hard rules. This approach addresses a critical gap in current AI adoption: retailers are increasingly asking vendors not whether they have AI, but what the AI actually decides and what it hands back to humans.

The framework also introduces a Decision Ledger, a complete audit trail of every dispatch decision showing who decided, what was known, what was chosen, and actual outcomes. For supply chain professionals, this represents a significant shift toward transparency and accountability in AI-driven operations.