The shipping and logistics industry has many operational complexities that make this business space a great candidate for the deployment of artificial intelligence technology. But many struggle when it comes to actually implementing AI technology in a manner that brings maximum benefit in terms of operational efficiency. This means that many AI implementations fall short of reaching their full potential in terms of ROI. So the question remains: How is AI being implemented in the shipping and logistics industry? And how do you deploy this technology in a way that will generate a strong ROI — one that actually increases over time?
Implementing AI in Shipping and Logistics
The shipping and logistics industry has many defined, repeatable processes which lend themselves to AI-powered process automations. Add machine learning to the equation and you have a process automation that actually improves itself over time, becoming increasingly efficient. Shipping and logistics process automations can take many forms, including some of the following.
Demand Prediction – The most profitable and successful shipping and logistics companies must accommodate fluctuations in demand. Machine learning-powered AI technology can be used to help predict changes in demand, allowing for greater agility and adaptability.
Freight Bills – Freight bill automations can be established, saving time, money and eliminating human error from the equation.
Route Optimization – Drivers can benefit from dynamic AI-powered route optimization. Machine learning and AI technology can account for traffic, weather and other factors when recommending a route.
Fleet Maintenance – Good fleet management is essential for success in the shipping and logistics industry, but it’s difficult to find a good balance in practice. AI technology can be used to predict problems and recommend solutions, including proactive measures such as maintenance.
Back Office Integration – AI technology can be used to facilitate back office integration in a variety of ways. Truck drivers must track their driving time, for instance, generating data that must be sent to back office platforms.
AI technology is also being used to create “smart” equipment. For instance, FedEx recently deployed a two-armed robot named DexR to load parcels onto delivery trucks. Artificial intelligence was used to automate the truck loading process with DexR, which means that humans can focus on more complex tasks. This is just one example of how AI can be used to automate warehouse tasks. Picking and sorting is another function that can be automated using machine learning and AI. Amazon has even developed AI technology that can identify irregularities and anomalies that can signal a defective product, flagging the item before it ships to the customer.
Deploying Machine Learning and AI in Shipping and Logistics
There are countless ways to deploy AI in the shipping and logistics business space. The key to success is to identify a problem, challenge or a process that represents an opportunity for improvement and then, develop AI technology to meet that need. The 7T development team uses this problem → solution approach as we deploy machine learning-powered AI technology. It’s a development strategy that holds the power to bring a healthy ROI to clients such as Simplex Group.
The Digital Transformation development team here at 7T is guided by the approach of “Digital Transformation Driven by Business Strategy.” As such, the 7T development team works with company leaders who are seeking to solve problems and drive ROI through Digital Transformation and innovative business solutions such as multimodal machine learning-powered AI implementations.