Logistics: The Aim of Targeting Artificial Intelligence

Logistics, an industry that relies heavily on labor and manual management, is facing a period of transformation with the advance of artificial intelligence (AI). As market demands evolve toward the paradox of instant high-volume delivery and personalization, AI has emerged from the tide of information systems, data analytics and internet connectivity.

Amazon is perhaps the most recurring example.  With a business model that ranges from the perception of infinite storage to expedited and infallible logistics, the company has placed itself at the forefront of the technology-based logistics race. Part of this is the investment in robots, such as Kiva models, used in its distribution centers, where the conventional dynamics of warehouse operations have been redesigned.

These are robots that bring complete shelves to workers, with process flows that have significantly reduced travel times and, above all, errors caused by humans due to repetitive activities. According to The Wall Street Journal, this innovation has allowed Amazon to process orders with high efficiency and in robot-human collaboration, creating a new standard for the e-commerce industry. And this is just one example of many that this company can provide.

Accurate, Timely

Talking about logistics would not be possible without mentioning parcel companies. Carriers such as UPS and DHL have implemented AI-based solutions to improve their operations. And this is not new; in 2013, Forbes announced that UPS had adopted the ORION (On-Road Integrated Optimization and Navigation) software platform, which, using advanced algorithms, determines the most efficient routes for the company’s drivers.

This platform is being used now together with NTPs (Network Planning Tools) and other telematic tools mounted on trucks that allow them to obtain data in real time and thus design improved delivery route models supported by AI. In short, all of this not only reduces operating costs but also improves customer service by ensuring faster and more accurate deliveries.

Another key component in logistics is ocean freight. The company Maersk, one of the world leaders in container transport, has also invested in AI to optimize maritime routes. The objective is to achieve “zero touch logistics,” which refers to the complete automation of logistics processes, where all operations, from order to delivery, are carried out without manual intervention.

Using advanced technologies such as artificial intelligence, machine learning, robotics and the Internet of Things (IoT), this approach seeks to increase efficiency, reduce errors and optimize the use of resources in the supply chain. Creating a logistics system that is more agile, accurate and cost-effective is the objective, providing proactive and real-time management that can anticipate needs and resolve problems before they occur.

Digital Polar Star

An interesting case is that of Rolls-Royce, which has been working on autonomous shipping technology since the early 2010s and announced last year its intention to launch its first unmanned ocean ships by 2025. As a first step toward this goal, it launched its Intelligent Awareness system for manned vessels earlier this year.

This system uses a network of cameras, LIDAR and radar, monitored by a central program that, using machine vision algorithms, searches for obstacles like other ships and sends automatic alerts to the crew. As part of its new agreement with Intel, Rolls-Royce will use Intel's 3D NAND solid state drives to store the data generated by this network (up to 1 terabyte per day) and Intel Xeon processors to analyze it. 

Beyond current applications, the trend points toward an ever-deeper integration of AI in logistics. From drones equipped with AI to monitor crops and make deliveries, to autonomous vehicles that can transport goods without human intervention, the horizon is full of possibilities.

However, the adoption and governance of AI varies by region and type of company. Countries with advanced technological infrastructures and a strong focus on innovation, such as the United States, China, and several European countries, are at the forefront. They not only have leading companies in the sector, but also an ecosystem of startups and research centers that constantly push the limits of technology.

Stated in this way, the development of an adequate infrastructure to implement AI should be considered at an early stage. This involves establishing a set of practices, policies and processes designed to manage and oversee the development, deployment and maintenance of AI applications in an efficient, safe and ethical manner. The above should be understood as an AI Government.

This should consider aspects such as establishing the framework and compliance of a system of standards in which they must consider AI Ops, which involve the application of artificial intelligence methods, practices and technologies to improve and automate IT operations, and MLOps, which help to standardize machine learning models between devices.

Large corporations, due to their resources and the scale of their operations, have been the first adopters of AI-based solutions. As technology becomes more accessible and solutions are more modular, small and medium-sized businesses are beginning to integrate AI into their operations, which in turn will strengthen supply chains and take logistics to levels that, until recently, would seem utopian.