Boosting efficiency: AI-powered logistics for e-commerce

Artificial Intelligence and logistics have now become inseparable. More and more companies are investing in the automation of logistics operations.

In these last few months, we have witnessed a profound transformation. The integration of Artificial Intelligence into our lives is having the same impact that the advent of the internet once had.

The application of Artificial Intelligence solutions in logistics is therefore essential to keep up with the times, in a market that is becoming increasingly demanding and competitive. This is why in this article we want to discuss the trends and opportunities that this new technology can bring to e-commerce.

AI in logistics examples and trends

Artificial Intelligence is progressively taking on an increasingly predominant role across all sectors, and logistics and supply chain are no exception.

Big Data analysis is just the tip of the iceberg of this technology. In fact, we will see how AI in e-commerce logistics can be used in various areas, from warehouse management to last mile logistics and delivery to the customer.

So, let's see discover the trends of AI for logistics:

1. robotics and warehouse automation;
2. transport and shipment planning;
3. product traceability;
4. predictive analysis and Big Data in business forecasting;
5. predictive maintenance;
6. predictive analysis of prices and costs;
7. customer experience management;
8. integration of emerging technologies.

1. Robotics and warehous

As we have previously discussed in detail, warehouse automation is one of the most strategic choices a company can make. By integrating sophisticated WCS (Warehouse Control System) software all logistics processes can be managed seamlessly, while robots are in charge of performing repetitive actions, such as picking or material handling.

This software allows robots to learn and adapt to the environment and perform tasks autonomously, without constantly requiring human intervention. In short, applying Artificial Intelligence to warehouse operations improves its management, enabling a reduction of human intervention and allowing people to shift to a more supervisory role. Furthermore, using software like ShippyPro offers companies the opportunity to automate their entire logistics process, starting from a comparison map of the best Italian carriers and foreign ones.

By analysing historical and real-time data, AI is able to guide companies through inventory management, eliminating waste or material and product shortages. This is because it can predict market demands and consequently evaluate which purchases need to be made.

2. Transport and shipment planning 

Planning transport routes is not an easy task, as different variables come into play:

• traffic data;
• road conditions;
• customer preferences;
• delivery times.

The ability to manage the large amount of data that is Big Data allows Artificial Intelligence applied to logistics to improve transport efficiency by analysing all this data in real time and comparing it with historical data.

In this way, it is possible to achieve an unprecedented optimization of routes, leading to a significant reduction in transit times and operating costs.

All this results not only into substantial cost savings for the company thereby enhancing profit margin, but as we will see later, it also contributes to an increased customer retention rate.

Lastly, systematic transport planning optimizes the use of energy, encouraging sustainable logistics practices.

3. Product traceability 

A customer who constantly knows where their parcel is, is a satisfied customer who trusts the brand.

To achieve this level of customer satisfaction, however, it is necessary for the company to know and have access to its shipping data. Tracking shipments effectively means implementing advanced technology, and leveraging AI in the logistics industry proves to be the most effective tool to achieve such information, for example using the IoT (Internet of Things).

There are devices equipped with sensors, software, and other technologies capable of connecting to the internet and obtaining information that was previously unimaginable. An example could be the degree of wear of a machine's components, monitoring the performance of vehicles or the condition of an object during transport.

AI can be used to track and trace shipments even in alternative sales systems, such as those where shipments are managed with Amazon FBA.

4. Predictive analysis and Big Data in business forecasting

Predictive analysis uses Big Data, this huge and heterogeneous amount of data, statistics, algorithms, and machine learning to predict behaviour or events.

This means that Artificial Intelligence can, for example, make demand forecasts, thus optimizing the production of product supplies, without risking the so-called overstock.

5. Predictive maintenance

The automation of logistics processes can also concern monitoring the performance of vehicles used for transport and of the machinery in the warehouse. Through sensors, sophisticated software and the IoT, Artificial Intelligence is able to collect data that can predict failures or malfunctions.

Based on this data, the company can provide preventive and proactive maintenance to reduce waiting times due to fault repairs, accelerating repair times and always keeping the entire supply chain efficient.

6. Predictive analysis of prices and costs

Among the Artificial Intelligence solutions for logistics, that of price and cost forecasting is among the most useful. Thanks to the amount of information that AI can process, it is able to estimate the prices of materials, as well as transport costs, and predict future price changes associated with logistics.

7. Customer experience management

Complaint management, e-commerce reviews, and even cart abandonment are all aspects that can be managed through conversational artificial intelligence, i.e. virtual assistants and chatbots that can interact with customers, providing them with real-time support regarding their orders.

8. Integration of emerging technologies

Artificial Intelligence and logistics are integrating more and more with other emerging technologies. The Internet of Things (IoT) that we have already spoken about, augmented reality and the blockchain are among the most advanced logistics trends.

Augmented Reality is a technology that shows the surrounding reality enriched with video information, for example sat navs that project service stations, speed information or speed cameras directly onto the windshield of the car.

The blockchain, on the other hand, enables more secure communication, even between the various parts that make up the supply chain.

Benefits of AI in logistics

As we have seen, AI for logistics is offering several opportunities for entrepreneurs who desire to improve their business. Here are the main advantages.

Reduction of operational costs. In the long term, according to statistics, the introduction of artificial intelligence can lead to a reduction of costs of up to 10% (McKinsey). Robotics, warehouse automation, transport planning, customer experience management, are all important aspects in logistics management which, once automated, allow a significand reduction of expenses. However, installing this technology can imply a significant investment, and this is why companies who wish to automate their supply chain may have access to various financial incentives.

Increased efficiency in the supply chain. The introduction of Artificial Intelligence optimizes the entire supply chain. It allows for more accurate strategic planning and better inventory management, enhanced plan production based on customer demand, better allocation of resources, etc. This can lead to a revenue increase of up to 4%.

Improvement of service quality and customer experience. Delivery efficiency leads to an improvement in the quality of service offered to customers. Among the most important advantages we find:

• reduced times;
• higher accuracy;
• delivery customization;
• advanced tracking and tracing.

These aspects contribute to a significant enhancement of brand awareness and customer loyalty.

Reduction of the environmental impact. Artificial Intelligence in logistics represents a great ally for environmental and sustainability issues. Here are some of the opportunities offered by this combination:

• optimisation of delivery routes, with consequent savings in fuel and obviously in emissions by reducing times and distances;

• support in the adoption of vehicles with low environmental impact, by verifying their characteristics and by analysing their performance, allowing companies to choose the most ecological ones;

• optimisation of resource usage and waste reduction through inventory analysis, demand forecasting and optimal warehouse management;

• improvement of energy management by monitoring the lighting and heating systems of the storage sites.

Conclusions

AI application in logistics is becoming increasingly popular. A growing number of companies are starting to exploit its potential to offer a more competitive, efficient service, and effectively address the demands of the present era.

It is expected that in the near future, e-commerce shipments will be ever faster and more efficient, will be carried out with new technologies such as drones and self-driving vehicles, or through the integration of sophisticated systems such as the Internet of Things, the blockchain and augmented reality like the Metaverse.

Companies just have to stay ahead and be ready to offer an efficient, fast and competitive service.

FAQs

What is AI for logistics?

Ai for logistics refers to the application of Artificial Intelligence techniques and technologies to enhance various aspects of logistics and supply chain operations. It involves leveraging computer systems, algorithms, machine learning models and processing large amounts of data such as Big Data to optimize and streamline processes.

What are the benefits of Artificial Intelligence for logistics?

Here are some of the main benefits that can be achieved by automating logistics processes with Artificial Intelligence:

• reduction of operating costs;
• increased supply chain efficiency;
• higher quality service and improved customer experience;
• reduction of the environmental impact.

How is Artificial Intelligence used in warehouse management?

Artificial Intelligence can be used in any area or activity of a warehouse:

• for inventory management to reduce the margins of human error and to analyse historical data for supply forecasts;
• for warehouse automation by introducing robots and implementing IT systems capable of managing them;
• for space management, maximizing space use through movement analysis;
• for article localization to reduce search times.

How can artificial intelligence improve product tracking in logistics?

Through the IoT (Internet of Things), sensors and sophisticated software, Artificial Intelligence can monitor products in real time during transport, detect the degree of wear of a machine's components, monitor vehicle performance or the condition of an item during its journey or at its storage site.