CHAPTER 1
Beyond Calculation: How Far Has AI Come in Logistics Decision-Making?
"Can AI independently decide where, whom, and how to deliver pharmaceutical products?"
When asked this, Professor Jin-Gyu Park, CEO of OmeletAI and faculty at KAIST’s Department of Industrial & Systems Engineering, responds without hesitation:
"Absolutely."
This isn’t an empty promise. Park not only asserts the claim, he demonstrates it. An AI system generating thousands of pharmaceutical delivery plans in just five seconds—then dynamically updating those plans in response to changing road traffic, absent delivery drivers, or new last-minute orders. In short: machines perform the calculations people can’t, while leaving human judgment intact.
In the logistics field, this structure isn’t entirely foreign. For decades, logistics has relied on a mix of instinct and experience. Field operators know that "Route A always clogs up," or "Drivers avoid that pharmacy because of its long waiting time." These aren’t just anecdotes—they’re patterns of tacit knowledge that haven’t been easily digitized.
But what if AI could learn that intuition? More precisely, what if it could absorb the decision-making logic behind human expertise? Park describes this shift as a transition from operations-based logistics to decision-based logistics. It’s a world where AI becomes more than a calculator—it becomes a partner in decisions.
To put it plainly: every day, logistics professionals ask themselves, "How do I ship today’s orders in the fastest, most efficient, least resource-intensive way possible?" OmeletAI offers a compelling answer.
In this article, we explore four innovations where AI is already reshaping the future of logistics: pharmaceutical distribution, food delivery, parcel box optimization, and even unmanned maritime vessels. We also examine Park’s view on what ultimately determines success—or failure—when AI meets the real world.