Artificial intelligence has become the defining buzzword of modern supply chain transformation. Yet for all the excitement, the question remains: How do you turn AI’s potential into measurable results?
At the CSCMP EDGE conference, Shanton Wilcox of NTT Data moderated a lively discussion with Vishwa Ram, vice president of data science at Penske Logistics, and Tim Long, industry principal for manufacturing and logistics at Snowflake, exploring what it means to get “beyond the hype.”
AI is a living system
For Penske Logistics, AI is not a one-time deployment, it’s an evolving ecosystem that must adapt to shifting business conditions.
“The value of AI sometimes does erode over time,” Ram explained. “There wasn’t a sudden failure of the model, but there was just a slow liquidation of results over time. That really highlights the importance of continuous monitoring, retraining, and governance because model drift creeps in and if you’re not tracking its performance against business metrics, it’s almost always too late.”
Ram described Penske’s “driver retention” model, which once significantly reduced overtime, but gradually lost effectiveness as the business changed. The experience reinforced his belief that companies must treat AI as a living system, ‘not a set-it-and-forget-it solution.’
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