5 Ways on How AI is Revolutionizing the Logistics Industry

AI has a pivotal role to play in revolutionizing the logistics industry.

Everything grew increasingly digital as a result of globalization; consumers began to buy more online and expect their products or services to be delivered faster and for less money. In today's fast-paced world, logistics and supply chains must adapt to quickly changing consumer demands. As per ML news, supply chains waste hours each day on paperwork, resulting in a yearly loss of more than $170,000. Using AI for some of the jobs is one approach to improve the issue. Transferring certain manual activities to machines can help alleviate the problem of paper-based paperwork while also increasing productivity. In this article, you will explore how AI is contributing to the logistics industry.

AI Impact on Logistics

Artificial intelligence has radically altered the logistics and supply chain industries. Here are five ways that AI-driven technology may help businesses enhance and innovate their logistics and supply chain operations.

1. Robotics

Robotics refers to the use of intelligent machines in the supply chain management process. As per Statista research, revenues of logistics service robotics would reach more than $6 billion in 2021. Robots can generally do routine operations such as delivery, transportation, storing, picking, packaging, and routing. The primary distinction between regular industrial robots and AI-assisted robots is that the latter can execute more complicated jobs without the need for human intervention. Smart robots may also evolve by learning new tasks and executing increasingly complicated behaviors. It means that this gear can partially, and in some circumstances completely, replace humans in the distribution process, making it more predictable, simple to regulate, and successful. Drones, for example, may transport a certain amount of load and can fly or move on land or water. RFID (radio-frequency identification) solutions can sort, identify, and deliver items through the warehouse autonomously. As a result, robotics in logistics can boost production while also making it easier for humans to manage the various phases of delivery.

2. Autonomous Vehicles

Autonomous vehicles have the potential to dramatically improve delivery efficiency. This technology has the potential to improve dependability, cost efficiency, and predictability. Even though we have yet to acquire completely autonomous delivery vehicles, it is just a matter of time. As technology advances, it is conceivable to anticipate that in the not-too-distant future, consumers will get their shipments without the need for human intervention. According to the Mckinsey research, autonomous vehicles, especially drones, will deliver over 80% of all packages. By overcoming transportation obstacles and inconveniences, this technology will improve the efficiency of the distribution process.

3. Computer Vision

Every vision system is made up of two major components: the camera and the "brain" computer that controls everything. Based on a sophisticated algorithm, it can detect objects, goods, particular activities, colors, and perform actions. This technology may be used to identify damage and increase productivity in the production process. Amazon, for example, employs a computer vision-based AI system to offload a trailer of merchandise in 30 minutes rather than the hours it would take without it.

Furthermore, computer vision-enabled systems can automatically detect damage, determining the cause of the damage, its severity, and taking steps to prevent future cargo mishaps. The loading and unloading of products is another application of computer vision. This technology not only recognizes and locates items and packages in the store, but it also does so autonomously. With this in mind, machine learning systems are extensively utilized to reduce customer churn, improve supply chain quality, and improve the delivery process's security.

4. Predictive Analysis

Any logistics firm must be able to function efficiently, deliver on time, and save transportation expenses. To accomplish this, an in-depth study based on historical data is required to detect risk trends, implement corrective steps, and generate projections. You can only dramatically enhance logistics operations, modify shipment patterns, offer on delivery, and forecast consumer behavior by utilizing predictive analysis. MHI Annual Industry Survey for 2020 stated that the percentage of logistics companies using predictive analysis took a flight from 17% in 2017 to 30% in 2019. It can not only improve supply chain visibility, optimize routes, and make tracking and planning shipments easier, but it can also identify unexpected circumstances and hazards. If properly implemented, it will considerably decrease operating expenses and assist businesses in making more informed decisions.

5. Big Data

Logistics, like every other business, generate a considerable volume of data. It would have been more difficult to handle all of this material without a well-maintained data management system. Companies can save money and avoid late shipments and deliveries by collecting data from multiple sources such as drivers' applications, devices, and systems, and assessing how various elements impact the delivery process. You may obtain insight into historical delivery statistics, driver ratings, and make changes using big data analytics. More than 91% of Fortune 1000 firms, according to the study, are investing in big data. Furthermore, AI-driven data analytics enables businesses to account for variables such as fleet maintenance schedules, vehicle sensors, inclement weather, and fuel costs. It not only provides drivers with destination ideas and helps them travel more effectively, but it also allows businesses to reduce logistical expenses on a route-by-route basis.

Conclusion

By bringing new methods of dealing with data and improvements across the whole supply chain, AI is changing logistics procedures. Predictive analysis, robots, computer vision, deep learning, and autonomous vehicles are examples of technology that can greatly improve logistics and supply chain performance. They have the ability to alter the way items are managed in warehouses, as well as optimize last-mile delivery and logistics networks. With this in mind, logistics and supply chain firms could consider these technologies as a means of enhancing efficiency and lowering costs.