How AI Is Solving the $100B Surplus Inventory Problem Nobody Talks About

Most manufacturers are sitting on millions of dollars of surplus inventory and have no idea what to do with it. In this first episode of Real World AI Talks by Just AI News, host Paulo Iñaki Palma sits down with Luke Crihfield, Senior Director of Revenue at Amplio Supply Chain, to break down how artificial intelligence is changing the way enterprise manufacturers manage, appraise, and sell industrial surplus assets. From AI-powered cataloging apps to automated appraisal engines, this conversation covers what AI can realistically do today in supply chain operations and where human judgment still has to lead.Luke explains how Amplio built a system that uses machine learning models to assess price ranges, liquidity, and logistics costs for thousands of SKUs at once, making surplus asset disposition faster and more transparent for enterprise clients. He also talks about the limits of AI in this space: why image recognition alone is not enough to catalog industrial machinery, and why an AI output is always a starting point for a decision rather than a final answer. If you want to understand how AI actually works in a real B2B environment, rather than in theory, this is the episode to watch.The conversation also covers how Amplio is using AI internally to improve its own revenue operations. Luke shares how his sales team uses a network of Claude-powered skills connected to Zoom, Gmail, HubSpot, and Google Drive to reduce administrative work and spend more time building client relationships. This is a clear, practical look at what AI-native revenue teams look like in 2025 and what separates genuine AI adoption from just using a faster version of old tools.Topics covered include: surplus inventory management, AI appraisal and cataloging tools, secondary market liquidity, B2B revenue automation, sustainability in manufacturing, the $11.1M Series A from Hitachi and Yamaha Ventures, and what the next generation of AI-powered supply chain platforms may look like.