AI In Logistics: Shaping The Future Of Supply Chain Management

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AI In Logistics

A logistics industry that once relied on manual labor and time-consuming processes is now being automated by artificial intelligence. AI in logistics is transforming into a streamlined machine where everything is predicted in advance. Clearly, traditional processes are being replaced by automated, efficient, and predictive ones.

Many businesses are exploring and applying AI to their businesses. More than half of logistics companies (58 percent) expect AI to become widespread and replace many logistics tasks, such as route planning and empty run avoidance. 

AI is also transforming warehousing and transportation and making targeted use of the technology to increase efficiency, quality, and productivity. In order to shed more light on Artificial Intelligence in logistics, let’s take a look at how AI is being used to significantly impact logistics. 

What is AI in Logistics, and What Does it Do? 

It is no secret that logistics has historically been a complex, manual industry. Most warehouse operations, such as picking, packing, and shipping, are manual. There were a number of challenges associated with the traditional approach.

However, with the emergence of AI, the logistics landscape underwent a significant transformation. Basically, AI in logistics is integrating artificial intelligence into supply chain management to streamline the process and revolutionize how goods move. Custom logistics software solutions can help you predict future demand, ensuring you have the right inventory on hand. 

As a result of the introduction of AI into logistics, the industry has changed dramatically, with experts predicting that logistics productivity will increase by more than 40% by 2035. AI has helped resolve some of the common challenges that slow down progress and made the journey smoother, proving how important smart technology is. 

Logistics and supply chain management have become more intelligent by analyzing traffic and weather in real-time to optimize delivery routes.

The use of AI in vehicles can also be used to predict potential maintenance issues, preventing breakdowns and delays that can be costly. The logistics industry is no exception to the use of artificial intelligence to automate tasks. AI-powered robots can automate warehouse tasks such as picking and packing orders, improving efficiency and accuracy.

A significant benefit of Artificial Intelligence in logistics has been its ability to streamline operations, reduce costs, and ensure that the supply chain runs smoothly, which in turn ensures that customers receive their goods on time and without any problem.

AI in Logistics Market Overview 

According to Straits Research, the global AI and logistics market size was projected at USD 7.96 billion in 2022. By 2031, it is expected to reach USD 238.89 billion, growing at a CAGR of 45.93%. 

ai in logistics market overview

AI in logistics is primarily being demanded due to the rapid growth of e-commerce and international trade around the world. International trade and e-commerce are both reliant on logistics. Growing internet penetration with high-speed internet connections is boosting the proliferation of IoT devices in the logistics industry, which simplifies AI implementation.

How AI is Used in Logistics: The Use Cases 

How AI is Used in Logistics

The use of AI in logistics and supply chains has transformed operations by automating mundane tasks, optimizing routes, strengthening security, reducing costs, and elevating customers’ experiences. Listed below are some use cases of artificial intelligence in logistics you may find useful. 

1. Demand Forecasting

demand forecasting

By 2035, artificial intelligence is expected to increase logistics productivity by more than 40%. In today’s world, being able to forecast where assets are needed is a huge advantage. AI can provide a roadmap to enhanced feasibility by connecting a multitude of databases along the transportation chain.

With AI-driven software, logistics companies can forecast demand up to 12 weeks in advance by asset type and location. They will gain insight into how to route rail and vehicles more efficiently, optimize ocean storage, and potentially avoid bottlenecks at ports or areas of common production delays. 

AI is being used in logistics to predict future demand so that businesses can optimize inventory levels, streamline supply chains, and minimize stockouts and overstock situations. Learn more about the inventory management software we work on, Orderhive.

2. Route Optimization

Traditional route planning methods in logistics are often static and do not take real-time conditions into account. AI can be used for route optimization to save time and money. It can also improve customer service by reducing delivery times.  

Route planning with AI can incorporate a wide range of variables, including traffic, weather, and construction. As conditions change, it can also constantly reevaluate routes. 

The use of AI-based route optimization has been shown to reduce fuel consumption by as much as 20% in some cases. Route optimization software based on AI is available in a variety of forms. You can leverage AI and ML development services to build your own software as per your business requirements. 

3. Warehouse Automation

The MHI annual industry report estimates that 60+% of businesses will use AI-powered warehouse solutions by 2026, up from 40% in 2020.

As e-commerce giants like Amazon offer same-day delivery, warehouse efficiency is becoming increasingly important. Many logistics businesses are already using AI-driven warehouse automation solutions, such as robotic pickers, inventory management systems, and smart sorting algorithms. This helps businesses automate repetitive tasks and optimize inventory management.  

For example, an AI system can track robots used to move inventory around in a warehouse and ensure they move the right items. AI can also be used to identify errors during the picking and packing of items. It can improve accuracy and reduce order completion time. Moreover, AI is useful for identifying inefficiencies in warehouses and monitoring warehouse conditions.

Take a look at our case study on eProcure, an ecommerce marketplace that automates the entire procurement process using blockchain technology. 

4. Predictive Maintenance

It is often difficult to prevent unexpected equipment breakdowns with traditional maintenance schedules, which are based on time or usage. This can lead to delayed shipments, unhappy customers, and increased operational costs. However, AI can help eliminate such issues by spotting them early on.

Machine learning algorithms are used to analyze data from sensors installed on equipment to predict maintenance needs. With this data, it is possible to spot patterns or anomalies that may indicate a potential breakdown, enabling preemptive maintenance and reducing unplanned downtime.

The use of AI in supply chain management is also improving damage detection. Using machine learning and computer vision, we can identify and classify damages in delivered goods and assets. The result is a quick resolution, a reduced loss, and a more satisfied customer.

5. Customer Service Chatbot

The customer service department plays a key role in logistics companies since customers may contact them if they experience delivery issues. Chatbots can handle a variety of low-to-medium-level call center tasks, including Requesting a delivery, Sending an order, Tracking shipment, or Responding to a FAQ.

A chatbot can also be used to analyze customer experience. You can build a better understanding of your customers’ experiences with AI logistics solutions.

6. Self-Driving Trucks

As companies seek to reduce costs and improve efficiency, self-driving or autonomous trucks are becoming more popular. Although the technology is still in its infancy, it has the potential to revolutionize the shipping industry by making it cheaper, faster, and more reliable.

Logistics can be transformed by self-driving trucks or cars by reducing heavy reliance on human drivers. The use of autonomous cars and trucks is likely to become a reality relatively soon 

It is only a matter of time before autonomous trucks appear on roads around the world. 

Companies like Tesla, Google, and Mercedes-Benz are heavily investing in the concept of autonomous vehicles. By 2030, however, only around 10% of light trucks will be autonomous, according to BCG estimates. 

7. Delivery Drones 

delivery drones

In logistics, delivery drones are useful machines for delivering products where ground transportation is not safe, reliable, or eco-friendly. Healthcare companies, especially those dealing with pharmaceutical products with a short shelf life, can reduce waste costs by using delivery drones.

In December 2016, Amazon began using AI-powered delivery drones to ship cargo around the world. Amazon reports that it has been able to make deliveries within 30 minutes so far. As a result of the use of AI-powered delivery drones, Amazon has also been able to reduce shipping costs and time, as well as improve delivery accuracy. There is no doubt the future of AI in logistics will be driven by drone deliveries, ensuring quick, safe, and reliable deliveries. 

Must Read: Digital Transformation in present-day Supply Chains

Examples of Companies Using Artificial Intelligence in Logistics 

Check out these three companies that are leveraging artificial intelligence in logistics and supply chain management. 

Amazon

Amazon, the world’s largest e-commerce company, is at the forefront of AI innovation in logistics and supply chain management. Using AI algorithms, the company manages inventory, forecasts demand, and optimizes logistics. Amazon’s supply chain is one of the world’s most efficient, thanks to its AI-driven system that anticipates customer demands, adjusts inventory in real-time, and optimizes delivery routes.

Ford

Ford Motor Company is using artificial intelligence to revolutionize its automotive supply chain. Using AI, the company anticipates and mitigates disruptions in the supply chain. Using AI for inventory management and parts procurement has significantly improved Ford’s manufacturing efficiency. 

Boeing

The aerospace giant Boeing is using artificial intelligence to optimize its complex supply chain. The use of AI algorithms helps predict maintenance needs, manage parts inventory, and ensure timely delivery of components. Aerospace manufacturing has benefitted from AI integration in terms of efficiency and safety.

Benefits of Implementing AI in Logistics and Supply Chain 

Artificial intelligence continues to revolutionize the logistics industry by expediting shipments. The use of artificial intelligence in logistics offers numerous advantages. AI can be used at every stage of the logistics process. AI can enhance logistics operations in a variety of ways, including:

benefits of implementing AI In Logistics
  1. Improved Efficiency and Productivity

Improvement in efficiency and productivity will always be the main advantage of Artificial Intelligence in logistics. A well-integrated AI system helps streamline processes, automate repetitive tasks, and optimize resource allocation, resulting in significant improvements in productivity and efficiency.

  1. Reduced Operational Costs

Another significant benefit of AI in logistics and supply chain is the reduction of operational expenditures. AI reduces operating costs and improves profitability by optimizing routes, minimizing fuel consumption, and reducing downtime through predictive maintenance.

  1. Safety Improvements

Artificial intelligence-based automated technologies improve warehouse management and worker safety. Manufacturers can use artificial intelligence to assess workplace safety data and alert them to potential dangers. The system is also capable of performing essential feedback loops and preventative maintenance, including updating operations and recording stocking parameters. Consequently, manufacturers are able to maintain warehouse safety and compliance quickly and forcefully.

  1. Increased Customer Satisfaction

Customer satisfaction is the ultimate goal of any business. Businesses are already using AI to improve customer satisfaction by tracking in real-time, estimating delivery times, and resolving issues proactively. With the help of chatbots, companies can improve customer satisfaction levels, which will result in more repeat business.

  1. Better Decision-Making

The use of AI-based automated technologies has proven to be highly beneficial for logistics businesses to make better decisions. Using AI-driven analytics, supply chain executives can make informed decisions and plan strategically for the future.

The Challenges of Implementing AI in Logistics 

AI logistics can be helpful, but only when companies understand the challenges of adopting the technology. By 2024, only 25 percent of organizations in the US, UK, and Germany have actually implemented artificial intelligence in logistics and supply chains. A number of factors contribute to the slow adoption of AI in transportation and logistics.

  1. Affordability

It is a universal truth that innovation is never cheap. Any change in an organization will always involve expenses. The larger the organization, the more the decision-makers will have to spend to implement new technology. 

The integration of AI requires upfront investments in technology, infrastructure, and potentially hiring AI-skilled personnel. Especially for smaller companies, this can be a significant financial hurdle.

  1. Lack of In-depth Digitization

AI adoption in logistics can be dramatically impacted by the lack of pre-adoption measures. In most cases, businesses encounter unsatisfactory results or misalignment between expectations and the final stage, leading to dissatisfaction.

The best way to avoid such a scenario is for executives to digitize corporate processes and lay a solid analytical foundation before investing in artificial intelligence.

  1. Insufficient Internal Expertise

AI adoption in transportation and logistics is hindered by a lack of employees who are experienced with using AI tools. Stakeholders and their areas of focus can benefit or suffer from innovation depending on the onboarding and communication process. 

To prevent the situation from happening, organizations need to combine digitization with clear and transparent adoption journeys.

  1. Privacy and Data Security Concerns

The security of sensitive data poses one of the most challenging aspects of integrating AI into logistics. To function properly, AI systems require massive amounts of data. This raises concerns about the security of this information.

  1. The Importance of Maintaining Human Oversight

In logistics, humans still need to rely on their intuition and judgment despite the efficiency of AI. Although AI excels at processing data, it may not always be able to make contextually relevant decisions. Maintaining human oversight in AI-assisted logistics is crucial to balancing automated efficiency and human insight.

The Future of AI in Logistics 

As AI and machine learning gain traction in supply chains and logistics, their market value is expected to reach $64 billion by 2030. We will witness further diversification of AI in logistics, given these promising numbers. There is a good chance that technology will continue to fill in various supply chain gaps and become more flexible to handle complex tasks in the future.

15% of retailers and consumer goods manufacturers said in a November 2022 EnsembleIQ study that they had implemented AI or ML to support their supply chain functions, while an additional 16% planned to add it in the next year or two.

The applications of artificial intelligence within consumer goods logistics are varied, and the future of AI in logistics promises great potential to help companies improve business outcomes. 

Artificial intelligence can automate complex logistics operations in a way that has never been possible before. Through optimized last-mile delivery and predictive analytics, logistics companies can reduce costs, increase delivery times, and optimize routes in real-time.

Summing Up

Embracing AI in logistics is the best way to improve your supply chain. We saw how AI has numerous applications in logistics and supply chains. This powerful technology is being implemented in companies all over the world. Many essential processes can be simplified and sped up with artificial intelligence. A routine task that takes a lot of time can be automated, improving efficiency and accuracy and reducing human error. 

There is no doubt that AI will revolutionize supply chain and logistics with the potential to optimize processes and provide a better customer experience. For businesses to effectively integrate AI into their operations, an AI development company can provide expertise and help.

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author
Niha Parmanandani
AUTHOR

A dynamic content writer with a degree in Mass Communication and Journalism, she specializes in writing for web and social media.  It is her passion to play with words and keep up with technology trends. Her passion for reading drives her to create engaging, educational, and inspiring content.

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