In the ever-growing and highly competitive logistics sector, automation has become indispensable, with the latest innovations in the form of artificial intelligence (AI) transforming business dynamics more radically than ever. The potential of this technology to improve productivity is almost unimaginable, positively affecting both the profitability and efficiency of businesses, as well as their ability to drive economic growth.
According to 2023 statistics from the US International Trade Administration, the UK AI market was worth more than £16.8 billion and is expected to reach £801.6 billion by 2035, while research Government figures suggest that around one in six UK businesses have adopted at least one form of the technology.
This growing adoption of AI opens up a range of possibilities for businesses in the logistics sector. By taking the data that can be gleaned from connected devices, AI can transform it into useful information that can be managed by robotic process automation (RPA) solutions. In this way, simple and repetitive tasks, usually performed manually by employees, are automated, generating opportunities to adopt more strategic, value-added tasks.
“Using artificial intelligence, we can accurately predict demand for goods and services and generate possible scenarios from current market conditions. This will enable logistics companies to efficiently allocate resources, plan transportation routes and optimize inventory levels, resulting in a significant reduction in operating costs that present a management challenge: fuel, labor and vehicle maintenance,” says Erick Martins (photo), Solutions Consultant at Descartes Systems Group.
“For industry players, having a tool that provides predictability, while allowing them to reduce costs and overcome possible obstacles in processes, is strategic and makes it an indispensable resource for years to come . Add operational efficiency and improve customer experience. “The application of AI to logistics operations is a trend that is expected to push the boundaries of the sector in the years to come,” he adds.
Implementing automation solutions in the areas of logistics and supply chain opens up a new world of potential for businesses, as they allow them to work with large volumes of data, analyze it in a timely manner reality, to spot trends and anomalies – and to make the resulting decisions. into tangible business benefits.
Here are four reasons to integrate connectivity tools based on AI and machine learning:
1. High return on investment by reducing mileage, fuel consumption and driving time, thereby increasing productivity. Using machine learning techniques, more deliveries can be made with fewer resources. vehicleswhich results in significant savings. These improvements not only affect the operational aspect, but also impact the administrative processes of logistics, including customer service, customer loyalty, availability and visibility for all relevant departments.
2. High availability combined with security. The Software-as-a-Service (SaaS) model is a trend that is increasingly being adopted by businesses. This approach eliminates the need to acquire, install and maintain software, since it only requires the payment of a monthly subscription that provides access to various features that are always updated and compliant with current regulations.
3. Integration into a single system. Integrating all platforms with a single provider offers several benefits, such as the ability to prioritize tasks based on their importance, including route planning, last mile execution, and delivery confirmation. The route planning tool combines information about customer restrictions, vehicles, service windows and routes, as well as the definition of rest areas and other details that allow you to create an optimal route.
4. Overall visibility of traffic (customer and order). Today’s technology provides real-time visibility into trucks, routes, orders and customers for all functions in every organization. This allows you to compare what is planned with what is actually executed, identify driver locations, and evaluate their performance. Additionally, analytical tools can be used to generate reports and dashboards, making route management and adjustments easier.
“Given the speed at which the segment is growing and the increasingly demanding needs of consumers, AI will soon be part of a strategic approach within companies aimed at optimizing efficiency, improving the quality of service and to maintain competitiveness in a market as dynamic and agile as logistics,” concludes Martins.
Conclusion
Implementing AI in logistics operations represents the next crucial step in modernizing and optimizing processes in this sector. With its immense potential, AI will be an indispensable tool in defining the future of transportation and logistics. However, it is essential to integrate these tools into existing systems and adapt processes to maximize their benefits.
It is essential to be ready to adapt, to acquire new knowledge and skills to prepare for the changes that AI will bring. Its strategic adoption will enable businesses to remain competitive and meet the demands of an ever-changing market.
