White robot using a pencil to write on a piece of paper

Erin Jernigan 11/2/23

In the ever-evolving world of logistics, companies are accepting the potential of artificial intelligence (AI). One fascinating area is generative AI, similar to ChatGPT, which holds the promise of cost savings and improved efficiency. While this technology excites many, logistics companies are cautious about introducing chatbots into their operations.

Notably, AI technology like ChatGPT has the ability to process vast amounts of information, recognize patterns, predict outcomes, and engage in human-like conversations. This technology can automate tasks such as tracking shipments, booking loads, and handling import declarations. However, the challenge lies in making sure this digital approach doesn’t leave customers upset, especially when they’re dealing with shipments worth millions of dollars.

Several companies, such as Freight brokerage RXO, trucking firm XPO, logistics tech provider Phlo Systems, and shipping company DFDS, are actively studying how generative AI could transform their customer service. Furthermore, by automating these tasks, they are striving to streamline their operations. Ultimately resulting in faster and more efficient systems for their customer.

The logistics sector is not the limit for generative AI. It’s already making strides in legal research, contract analysis, customer support, and more. For logistics companies, the goal is to enhance forecasting, procurement, inventory management, and shipping decisions. While it’s not a perfect solution, this technology’s ability to provide custom, real-time responses to customer inquiries is seen as a game-changer.

Yet, there are limitations. Generative AI’s performance depends on the quality of the data it’s trained on, and it’s not immune to errors. Companies are also wary of using proprietary data or customer information to train these systems, raising security concerns.

In the logistics world, where handling large shipments is a complex process using various modes of transportation, the stakes are high. As a result, supply chain decisions are sensitive, and reliability is very important. Using generative AI here requires a delicate balance, as RXO’s Jared Weisfeld points out. He emphasizes the need for a hybrid approach, combining chatbots with human interactions for a smoother experience.

To gain trust in this technology, supply-chain managers must be certain of its reliability, especially when dealing with orders, inventory management, and supplier negotiations. Tight governance and complete clarity around AI and data usage are essential.

XPO, for example, plans to train an internal ChatGPT-like bot. It will help customers track freight, obtain rate quotes, and create pick-up requests while ensuring data privacy and relevancy. Phlo Systems is already using AI-powered chatbots to handle customs declarations, making processes more efficient and improving customer interactions. DFDS is looking into generative AI’s software development capabilities, potentially opening the door to future customer support improvements.

The journey toward AI integration in logistics is indeed happening, offering exciting possibilities. As technology continues to advance, the industry’s path toward automation and improved customer service is becoming increasingly clear. With a careful approach and a strong focus on customer satisfaction, logistics companies, without a doubt, unlock the true potential of AI.