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 before. The potential of this technology to enhance productivity is almost unfathomable, positively affecting both the profitability and efficiency of companies, as well as their ability to foster 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 grow to £801.6 billion by 2035, while government research suggests that around one in six UK businesses has embraced at least one form of the technology.
This growth in AI adoption opens up a range of possibilities for companies in the logistics sector. Taking the data that can be gleaned from connected devices, AI can transform it into useful insights to be managed by Robotic Process Automation (RPA) solutions. In this way, simple and repetitive tasks, usually performed manually by employees, are automated, which generates opportunities to embrace more strategic value-added tasks.
“With the help of Artificial Intelligence, we can accurately predict the demand for goods and services and generate possible scenarios from current market conditions. This will allow logistics companies to allocate resources efficiently, plan transportation routes and optimise inventory levels, which results in a significant reduction in the operating costs that presente a management challenge: fuel, labour and vehicle maintenance,” says Erick Martins (pictured), Solutions Consultant at Descartes Systems Group.
“For players in the sector, having a tool that offers predictability, while allowing them to reduce costs and overcomes possible hurdles in processes, is strategic and makes it an indispensable resource for the coming years.” Adding operational efficiency and improving customer experience. “The application of AI to logistics operations is a trend that should expand the frontiers of the sector in the coming years,” he adds.
The implementation of automation solutions in the areas of logistics and supply chain opens up a new world of potential for companies as they allow them to work with large volumes of data, analysing it in real time, spotting trends and anomalies – and making decisions that result in tangible business benefit.
Here, therefore, are four reasons to incorporate AI and machine learning-based connectivity tools:
1. High return on investment by reducing mileage, fuel consumption and driver time, thus increasing productivity. Thanks to machine learning techniques, more deliveries can be made with fewer vehicles, resulting in significant savings. These improvements not only affect the operational aspect, but also have an impact on the administrative processes of logistics, including customer service, customer retention, availability and visibility for all departments involved.
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, as it only requires the payment of a monthly fee that allows access to various functionalities that are always updated and in compliance with current regulations.
3. Integration into a single system. Integrating all platforms with a single provider offers several advantages, such as the ability to prioritise tasks according to their importance, including route planning, last-mile execution, and delivery confirmation. The route planning tool combines information on customer restrictions, vehicles, service windows, and routes, as well as the definition of rest stops and other details that allow you to create an optimal route.
4. Global visibility of traffic (both customer and order). Today’s technology offers real-time visibility into trucks, routes, orders, and customers for all functions of every organisation. This makes it possible to compare what is planned with what is actually being executed, identify driver locations and evaluate their performance. In addition, analytical tools can be used to generate reports and dashboards, facilitating route management and adjustments.
“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 with the aim of optimising efficiency, improving service quality and maintaining competitiveness in a market as dynamic and agile as logistics,” concludes Martins.
Conclusion
The implementation of AI in logistics operations represents the next crucial step in the modernisation and optimisation of processes in this sector. With its immense potential, AI will be an indispensable tool defining the future of transportation and logistics. However, integrating these tools into existing systems and adapting processes to maximise their benefit is key.
It is essential to be willing to adapt, acquire new knowledge and skills to be prepared for the changes that AI will bring. Its strategic adoption will allow businesses to stay competitive and meet the demands of an ever-changing and evolving market.
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