AI In Supply Chain: Why Data And Context Matter

Valentina Jordan (Nauta) discusses why data, context, and operational knowledge are critical to unlocking the value of AI in supply chain operations.

Aug 12, 2026

Artificial intelligence is dominating conversations in supply chain today. Every software vendor seems to have an AI story, and every executive is being asked about their AI strategy. But amid all the excitement, many organizations are discovering that implementing AI is much harder than simply plugging a large language model into an ERP or supply chain application. Data is fragmented, business processes are complex, and without the right operational context, even the most advanced AI models can produce recommendations that are incomplete, impractical, or simply wrong.

So, what does it really take to unlock AI’s potential in supply chain operations? That’s the main question I discussed with Valentina Jordan, CEO and Founder of Nauta, during a recent episode of Talking Logistics.

The First Half of 2026: What’s Changed, What’s Worked, and What’s Next

The first half of 2026 has been anything but predictable. Tariffs, geopolitical tensions, AI advancements, changing transportation market conditions, and other developments have created new challenges — and new opportunities — for supply chain organizations. As we reach the midpoint of the year, we’d like to understand what has had the greatest impact on your organization, what has surprised you, where you’ve made the most progress, and what priorities will shape the months ahead.

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