Agentic AI and the $706B Returns Dilemma
Agentic AI and the $706B Returns Dilemma
Publish Date: 2026-05-15 00:50:00
Source Domain: www.supplychainbrain.com
- Costly Returns Impact: Returns and shrink cost retailers $796 billion, with $706 billion in return volume and $100 billion lost to fraud and abuse. AI and connected data can mitigate these losses.
- Agentic AI in Returns Management: Agentic AI can expedite internal workflows, helping analysts manage fraud by identifying incidents and guiding quicker actions without human intervention.
- Multi-Layered AI Approach: Effective AI in returns management involves a multi-layered strategy that uses data foundations, machine learning for decision-making, and agentic AI to enhance efficiency and accuracy.
- Data Foundation Importance: For AI to succeed in returns management, retailers must centralize and unify omnichannel consumer data, including unique identifiers and behavior patterns linked across various sources.
- Consumer Perception and Transparency: Retailers must maintain consumer trust by being transparent about AI’s role, as consumers prefer human judgment, but AI must operate within defined human-led rules and provide a real-time view of actions.
- Shift to Real-Time Decision Making: Agentic AI enables immediate identification and action against suspicious returns, updating inventory and logistics data in real-time for more responsive supply chain adjustments.
- Restructuring for AI Integration: Retailers, advised by firms like BCG, are adjusting their operations to better integrate agentic AI, aiming to align all organizational parts towards reducing losses and enhancing consumer experience.
- AI’s Role in Fraud Reduction and Logistics: AI has proven essential in curbing return fraud and streamlining logistics, with agentic AI promising to elevate these benefits through more proactive and real-time management.
