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How AI and ML are Transforming Logistics
How AI and ML are Transforming Logistics

January 9, 2023

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New technologies and technical advancements are constantly helping us progress with improved performance and convenience. The way we network and connect is also redesigned every day using modern technologies like Artificial Intelligence (AI), Machine Learning (ML), Big Data, and cloud systems. While all industries are greatly benefitting from new-age technologies, the organizations that come under the logistics sector are greatly influenced by the invasion of AI and ML.

This article will give you a clear idea of how AI and ML are positively changing the logistics industry's working style and helping logistics companies grow faster.

Adoption of AI and ML

Role of AI & ML in Logistics

In the era of digital logistics, all structured/unstructured data collected from various sources are analyzed using AI and ML for meaningful insights and strategy planning. Said that, let’s find out the roles of both artificial intelligence and machine learning separately before we get into the positives they bring to logistics and the supply chain.

Artificial Intelligence is a game-changer in logistics operations as the technology comes with many benefits including accuracy, cognitive automation, reduced costs, and less time consumption. The key role of AI is to automate mundane tasks and predict what’s coming. Moreover, route optimization and costs of shipping are the other two valuable pros of using AI in logistics.

AI is set to boost the productivity of logistics companies by more than 40% by 2035.
 

Role of AI in Logistics


Fast-developing logistics players are smartly using AI to transform warehouse operations such as tracking, locating, and moving inventories. This is possible because of the ability of AI to collect and analyze information and process inventory. Also, thanks to AI, robots are already in use for performing warehouse jobs with high precision and quality.

Next, the role of machine learning in logistics is to analyze huge amounts of diverse datasets to smartly plan demand and supply, customize, and optimize supply chains. Using Ml algorithms, logistics companies can figure out the important factors that can imply what’s better for the future and find out the risks in advance.

Machine learning has greatly molded the digitization of logistics and this has largely helped in reducing mistakes during the delivery of goods. Planning and scheduling have become more convenient within the industry and this is a prominent way to clear out complications that are acting as barriers to supply chain processes.

You might also be interested in reading “AI ARTIFICIAL INTELLIGENCE IN AUTOMOTIVE INDUSTRY: WHAT THE FUTURE HOLDS

Transformation in Logistics using AL and ML
 

Now that you know better about the roles of AI and ML in the logistics industry, let’s follow it up with the major transformations that are brought by the technologies. The below-given are some of the AI/ML practices that are greatly supporting the smooth functioning of logistics.

Remote Asset Tracking

A remote asset tracking system can improve the quality of supply chain management by letting you keep track of your goods, and their storage time, and optimize the shipping costs. The benefits of using an asset tracking solution include increased profits, reduced waste, better protection of goods, and top-quality management. Searching for a product or equipment becomes very simple with asset tracking and this is because of the use of historical data and analytics. Decision-making will also become easier for companies that use remote asset tracking.

Enhanced Customer Experience

Logistics companies always try to please their customers in all possible ways and it is healthy to do so for any business. Status updates, package tracking, and responsive chatbots are important factors that users need to satisfy customer experience. All these customer service features come to play with the power of artificial intelligence which elevates overall satisfaction.

Personalized product suggestion that happens as a result of analyzing customers’ search and shopping history is another way to bring more interest in customers. Every customer wants to be treated in a special way and AI has paved the way for personalized service using stored data.

Logistics Demand Prediction

It is now possible to predict the future demand for services and products in logistics through the use of machine learning. Algorithms that are fed with clean datasets have the ability to identify trends and patterns for forecasting the needs of customers and markets. The predictions are more or less accurate, helping companies make informed decisions and draw a successful future plan.

By collecting comprehensive data and implementing AI with machine learning, organizations can do better at estimating capacity, identifying shortages of goods, statuses of suppliers, and more. These valuable predictions help in a great way when companies start to strategize their moves and how they look out to grow.

Warehouse-capacity Optimization

Warehouse management plays a key role in the logistics sector for a smooth supply chain process. Businesses are welcoming the latest technologies to keep track of what’s happening in a warehouse, starting from its capacity status to every other particular detail. Optimizing a warehouse has become easier than before with the help of sensors that are installed to up-to-date notifications about the capacity of warehouses.

The ease at which companies manage their warehouse capacity, whenever and wherever they want, is greatly modifying the logistics business field. This is definitely one of the many big advantages of using AI with ML in logistics.

Real-time Fleet Management

Regular real-time monitoring of trucks and driver behaviors can come in handy for smart management and quick decision-making. Fleet tracking in the logistics industry lets businesses collect data easily about several small yet important factors like empty truck miles, transparency of truck locations, fuel costs, and more.

The habit of real-time fleet monitoring will give you a clear view of how to solve common fleet issues such as maintenance, fuel costs, and the position of assets. The main intention of using a real-time fleet management system is to optimize commodity transportation for better performance of the logistics company.

To know more about fleet management in Logistics, read “ IMPACT OF IOT IN FLEET MANAGEMENT

Product Inspection

Using AI, businesses are able to identify damaged products that can bring down the satisfaction levels of the customers who are valued the most by any business. Computer vision using AI is a popular tool that quickly inspects the quality of products that are ready to be dispatched. This avoids all the future damages that might happen because of inaccuracy in product quality checks.


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Inspirisys has been achieving excellence in empowering enterprises toward digital transformation with the help of contemporary technologies for more than 25 years. The company is part of CAC Holdings Corporation—a Japanese company with a proven track record in providing top-quality solutions and services across several industries, including BFSI, telecom, and government/PSUs. Inspirisys' portfolio of services and solutions includes infrastructure management, enterprise security & risk services, cloud, IoT, and product engineering & development.

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