Utilizing Artificial Intelligence in Japan’s Logistics Industry

Given artificial intelligence’s transformative quality, Japan’s logistics industry can potentially utilize this tool to address social issues.

January 2022 , by YCPS Marketing & Communication Group

Given that Artificial Intelligence (AI) has played a pivotal role within industries that operate in digital spaces like tech and finance, trends suggest that the same benefit can be extended to other industries and their processes. Specifically, technological solutions centered around AI may help address long-standing issues in areas such as construction, manufacturing, and building maintenance. In the context of logistical operations, AI technology will be advantageous in intralogistics, trunk line logistics (B2B), and the last mile (corporate-individual)—something that is already being explored in Japan’s logistics industry. 

To understand how Japan’s logistics industry can leverage the implementation of AI technology, read this excerpt from our white paper The Future of Technology in Social Infrastructure, an English translation of our original Japanese publication, which can be read in full here.  

Since the 2010s, the use of AI technology for large-scale data has been greatly promoted in the web domain, including with Google, Apple, Facebook, and Amazon (collectively known as GAFA), and in the financial domain that includes trading operations at securities companies and credit evaluation and risk management in banks. These industries are characterized by the fact that they have already accumulated a vast amount of digital data and have established standardized operations using IT systems. 

AI technology, which has been developed mainly in the aforementioned areas of digital space such as the Web and in finance, will be transferred to more “physical” areas such as manufacturing, distribution, and energy in the future. Currently, most of the applications of AI technology in social infrastructure are in the R&D and technology verification stages. However, as social issues such as the aging of public infrastructure and the decline of the working population become more serious, the social implementation of AI is expected to progress steadily. 

Conditions to Reach Social Implementation of AI 
In order to utilize AI in the physical domain, it is important to create a foundation for the accumulation of data and standardization of operations, so it is expected to take several years from the start of consideration to implementation. Looking back on history, it took many years for the steam locomotive—that has now become a synonym for the Industrial Revolution—to be implemented in society (it took 100 years from the development of Newcomen’s steam engine to the practical application of Stevenson’s steam locomotive), and it is believed that the social implementation of AI will proceed in a similarly gradual manner. Just as chemists and mechanical engineers worked together to contribute to innovation during the Industrial Revolution, business consultants and AI engineers will work together to reform business operations in the future. 

The social implementation of AI is expected to progress gradually through the maturation of technologies and markets, similar to the steam engine technology during the Industrial Revolution. In the process of social implementation, the key is not only AI algorithms, but also the availability of human resources and digital data to promote social implementation. 

Current and Future Landscape of Logistics & Tech 
In recent years, the increasing demand for transportation due to the expansion of the e-commerce market, combined with the shortage of manpower in the logistics field, has increased the workload of the logistics industry to the extent that it has been called a “logistics crisis.” In 2017, a similar situation called the “courier crisis” arose as a symbol of this “logistics crisis.” In addition, manufacturers, who consider logistics as a lifeline for their business, are also facing issues such as increased transportation lead times and soaring costs due to the logistics crisis and are required to re-examine their logistics strategies.  

In recent years, the introduction of AI, Internet of Things (IoT), and other technology has been attracting attention as a solution to these emerging issues. In this chapter, we will examine the issues surrounding logistics, clarify the factors behind these issues, and analyze how companies in the logistics industry should utilize technology in the future. 

Challenges in the Logistics Field and Tech Solutions 
In what has been called the “logistics crisis,” companies that make their living in logistics are facing a variety of challenges in warehouse logistics, trunk line logistics, and the last mile. As labor shortages worsen, labor-intensive solutions to these challenges are reaching their limits, and efforts to utilize technologies such as AI and IoT have begun. The relationship between the overall issues and the use of technology, including those still in the research stage, can be summarized as follows: 



Solutions Through Technology: 

Trunk Line Logistics (B2B) 


Solutions Through Technology: 

The Last Mile (Corporate-Individual) 


Solution Through Technology: 

So far, we have discussed the challenges of the logistics industry in recent years and the growing potential for the use of technology within the industry. The logistics crisis has had a major impact on manufacturers as well, and it is important to view issues in the logistics network as a management priority, rather than leaving these issues to logistics subsidiaries or contractors. In addition to considering the introduction of technology, it will be effective to develop a logistics system that is optimal for the sales channel structure, such as reviewing procurement and inventory management, and relocating logistics bases in preparation for demand fluctuations.

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