Square Insights What Are the Differences Between AI Agents and Generative AI in the Logistics Industry?

Key Summary
Generative AI can be defined an “AI that generates” new content, such as new text and images, based on content it learned.
AI Agent refers to an “AI that operates” predefined goals by designing plans and performing the process.
The key is that AI performs tasks on its own, not by a human.

1. How Far Has AI Come?

Artificial Intelligence (AI), considered one of the core technologies of the Fourth Industrial Revolution, has already established itself as a strategic asset in the logistics industry. Beyond automating repetitive tasks, AI analyzes and predicts vast amounts of logistics data, enabling more sophisticated supply chain operations. Particularly in today's world, where the complexity and volatility of global supply chains are intensifying, AI is being evaluated as a core driver not only for productivity improvement but also for crisis response and customer experience innovation.

2. Generative AI: Automation of Communication and Content

Generative AI is an artificial intelligence technology that learns large amounts of data to create new content or information. Generative AI expands the scope of usage from daily information search, such as text-based search, image and code creation, to creative content creation. Based on the prompt, the AI creates a creative outcome. Representative tools include ChatGPT, Perplexity, Gemini, and Midjourney.

In the logistics industry, the use of Generative AI is primarily focused on the areas of communication and content automation. For example, it demonstrates high efficiency in tasks such as customer support, email writing, translation, and summarizing internal reports. Cello Square responds swiftly to customer inquiries with an AI-based chatbot and provides real-time tracking information and service guides in natural language.

Additionally, given the large number of global customers, utilizing AI-based translation features to lower the barriers of multilingual communication is one of the important points. In this way, generative AI contributes to enhancing the internal productivity of logistics companies and maintaining more agile and consistent interactions with customers.

3. AI Agent: The Emergence of “Working” AI

Meanwhile, a technology that has recently gained attention is an AI Agent, more advanced than generative AI. An AI Agent is an autonomous system that goes beyond simply providing information by establishing its own plans and performing necessary actions based on predefined goals. If a generative AI is a “responding AI,” then an AI Agent is a “working AI.”

While existing generative AI was based on static prompt-response interactions, an AI Agent consists of the following components:

• Perception: Situation awareness

• Planning: Establishing strategies to achieve goals

• Action: Performing actual tasks

For example, if a customer asks, “Tell me the fastest air transportation schedule for this week,” a generative AI would understand the question and provide simple information. In contrast, an AI Agent would analyze the customer’s request, search for each airline and shipping conditions, derive the optimal route based on real-time data, and even proceed with automated booking if necessary.

This is more than simple task automation, demonstrating the arrival of an era where AI autonomously performs parts of actual business operations.

Source: 『Hype Cycle for Artificial Intelligence 2025』 published by Gartner

At the Gartner IT Symposium held in September, an AI Agent and AI-ready data were highlighted as the two core technologies expected to develop most rapidly at the 2025 Gartner AI Hype Cycle. The focus is shifting from an approach centered on generative AI (GenAI) to foundational technologies that support sustainable AI, such as AI-ready data and AI Agents. ^[1]

When examining the Supply Chain & Logistics sector specifically, Gartner predicts that by 2030, 50% of the SCM industry will use intelligent agents to execute autonomous decisions within their ecosystems. ^[2] Additionally, IBM announced that 70% of executives believe the introduction of an AI Agent in procurement and dynamic sourcing will enable employees to perform more in-depth analyses by automating operational processes by 2026. ^[3]
Companies are already developing and utilizing AI Agents by leveraging AI technologies and techniques from LLMs to perform complex tasks. Many industries are actively considering and adopting the next stage of Generative AI, which is an AI Agent.

4. How an AI Agent is Used in the Logistics Industry?

The logistics industry has a relatively lower level of system standardization compared to other industries, and it is hard for the logistics industry to apply technologies due to laws and diverse regulations. Also, AI Agent utilization lags in comparison to other industries.

An AI Agent can not only analyze and estimate data, but also recognize the current status and make judgments based on data accumulated so far, making optimal decisions and automating the execution. Therefore, it can be applied or utilized in diverse tasks of the logistics industry. In industry, it analyzes tracking data and detects lanes expected to be de delayed, then recommends alternative routes or preemptively sends notifications of delay to customers.

• Risk Response: In case of port strikes and bad weather conditions, it suggests alternative routes and automatically changes those based on real-time data

• Operation Automation: Check inventory in a warehouse, placing orders for short-stocked items, and appropriately distributing surplus items.

• Customer Response: An AI Agent handles cargo location tracking and shipping schedule changes, not by a human

In other words, an AI Agent is regarded as a “structure that behaves and judges by itself” by using basic and new data, covering from preventing accidents, making operations efficient to advancing customer services.

5. How about the AI Agent of Samsung SDS?

Companies are already adopting AI Agents in their services. Samsung SDS also utilizes an AI Agent in various tasks, leading the automation in the work process.

Local Transportation

• Agent managing dispatch

• Agent managing visibility

• Agent managing settlement

International Transportation

• Co-Pilot processing documents

• Agent managing risks

Warehouse Management

• Agent optimizing inventory

• Co-Pilot optimizing operators’ workflow

The logistics industry has long been challenged by uncertainties and operational inefficiency. However, the answer for those is an AI Agent that can overcome these limitations. In addition to analyzing and creating data, an AI Agent that judges and executes on its own is innovating the overall industry with risk responses, operation automation, and customer responses. Samsung SDS is one step ahead in providing services by applying AI Agent in local transportation, international transportation, and warehouse management. We will continue to be a reliable digital logistics partner whom customers can trust. Details of each area will be presented in the next article.

6. Future of Logistics: What’s Next?

AI technologies are moving past being a mere tool and are transforming the very paradigm of logistics businesses. Suppose an AI is fully in charge of or supports the entire process from customer responses, data analysis, decision making, to execution. Companies can focus more on strategic tasks, and customers can enjoy faster and more precise services.

To take the lead in the AI-based logistics ecosystem, Cello Square is evolving as an intelligent logistics platform that combines Generative AI and an AI Agent. The ultimate goal of Cello Square is to provide more rapid, simpler and smarter logistics services that customers desire through the “platform where AI is working.”

[Main Takeaways]

• ✅ Generative AI is good at communication and content

• ✅ AI Agent excels at designing and executing a plan

• ✅ Where the two technologies meet, standards of future logistics will be born.

[References]
[1] Gartner Hype Cycle Identifies Top AI Innovations in 2025.
https://www.gartner.com/en/newsroom/press-releases/2025-08-05-gartner-hype-cycle-identifies-top-ai-innovations-in-2025
[2] Scaling supply chain resilience: Agentic AI for autonomous operation, April 2025
[3] McKinsey Technology Trends Outlook, July 2025

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