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Index/Ops/Supply Chain Optimizers
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Inside American Eagle's AI-Driven Logistics Optimization

Supply Chain Optimizers · 2025-06-19 · 26 min

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Topics in this episode

Supply chain optimizationAI in retail logisticsAmerican Eagle Outfitters techGabriella Runnels interviewretail forecasting algorithms

Episode notes

Host Diego Solorzano sits down with Gabriella Runnels, Principal Data Scientist at American Eagle Outfitters, to explore how AEO combines tried-and-true mathematical optimization with cutting-edge AI to solve complex supply chain challenges. Learn how the team built four interconnected apps to slash costs, improve service levels, and even offer these capabilities to smaller brands via Quiet Platforms. Gabriella also shares her philosophy on change management, data quality, and why the future belongs to supply chain professionals who leverage AI without losing human creativity.

Related episodes across the Index

Other episodes covering the same guests and topics, from across The B2B Podcast Index.

  • Pickle Robot is on a mission to automate global supply chains with AI and RoboticsThe Robot Industry Podcast · on Supply chain optimization82 / 100
  • Ep 48: How To Build A Recession-Proof Brand With Your Principles - Andy Fallshaw from Bellroy [ Part 2]Ecom Alphas · on Supply chain optimization82 / 100
  • Nimbus: How a UK-Based Start-up Is Building Enterprise AI for the Next Generation of BusinessThe Marketing & AI Podcast: The MAP · on Supply chain optimization80 / 100
  • How Private Equity Is Buying Up Franchisee NetworksThe Buyout Show with Fexingo · on Supply chain optimization76 / 100
  • Ep. 131: AI Is a Tool, Not a Search Engine#shifthappens in the Digital Workplace Podcast · on Supply chain optimization76 / 100
  • What It Really Takes to Scale Generative AIData Analytics Chat · on Supply chain optimization73 / 100

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  • Global Logistics Across Borders: Navigating Clinical Trials, Compliance, and Complexity74 / 100
  • How to Avoid Chokepoints and Build Supply Chain Resilience71 / 100
  • Data Rich But Insight Poor: How to Optimize Multi-Echelon Inventory81 / 100
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