In recent years, various industries have been accelerating the development and adoption of ‘AI applications’, applications that run on devices such as PCs, smartphones and tablets, utilising rapidly developing AI technology.
AI technology enables advanced processing such as data analysis, prediction and decision-making, but how is it being used, developed and introduced in various industries?
AI technology has begun to be introduced in various industries
AI technology has developed rapidly in recent years and is being introduced in a variety of industries, with many companies actively developing and introducing AI at an accelerated pace, as it can help improve operational efficiency, reduce costs and promote business growth.
In general, looking at the status of AI adoption, the IT and manufacturing industries introduced AI technology at a relatively early stage due to the affinity between the industry's structure and constitution and AI, and have seen its benefits. It is fair to say that it is now used on a daily basis.
Meanwhile, in recent years, other industries have also been actively developing and introducing AI applications specific to their respective industries, and AI will become even more familiar in the future.
While all industries are promoting the introduction of AI, there is a clear distinction between what AI technology can and cannot do at the current stage, which is both a common understanding among industries and one of the major challenges.
It goes without saying that the greatest benefit of introducing AI at the current stage is the fast and accurate processing and analysis of large amounts of data. In today's paperless society, which has accelerated over the past few years, every industry has big data.
How to utilise big data accumulated from the past for marketing is a recent trend in the marketing industry. This is one of the advantages of introducing AI, which has sufficient processing power even in its current state.
Challenges with current AI as seen in ChatGPT and Midjourney
The greatest advantage of introducing AI at the current stage is that it can analyse large amounts of data that cannot be processed by humans in a short period of time and make highly accurate decisions. It can also perform tasks efficiently based on certain rules, and AI-equipped robots are replacing them in the industrial sector, for example, to improve the efficiency of simple and hazardous tasks and reduce risks.
In recent years, AI applications such as ChatGPT and Midjourney have become a hot topic in the general public, but before the advent of these applications, AI was considered unsuitable for artistic and creative fields.
However, ChatGPT and Midjourney have solved this disadvantage. For example, ChatGPT and Midjourney can generate natural, high-quality illustrations and images, although not entirely from scratch, based on vast amounts of historical data.
This means that in artistic and creative fields that require a certain level of skill and expertise, such as photographers and illustrators, it is possible, to take an extreme and exaggerated example, for someone with zero knowledge, who has never handled a still camera or drawn a picture before, to use ChatGPT and Midjourney. Midjourney, it is now possible for someone with zero knowledge, who has never handled a stills camera or drawn a picture, to produce professional quality work.
On the other hand, there are issues at the current stage of AI that have become apparent with the advent of AI applications such as ChatGPT and Midjourney. For example, there are plagiarism and copyright issues in the publishing industry: when illustrations and images are generated by ChatGPT and Midjourney, it is difficult to know where the rights lie.
Normally, the creator of an illustration holds the copyright. However, if the illustration is generated by ChatGPT, which generates images from a vast amount of past data, there is a possibility that some rights may be included in the collected data, as it is not generated from scratch. Therefore, can the creation generated by ChatGPT or Midjourney be legally and morally regarded as the right of the creator? This is a challenge for the current use of AI in the publishing industry.
This is an example from the publishing industry, but the same issue is also true in the academic world, which deals with research papers, etc. Since copyright naturally exists in relation to data, including research results, such rights-related issues are likely to be raised in the introduction and use of AI.
In addition, according to the experts, there are other issues to be faced when introducing AI, such as solving atypical problems, understanding emotions and human relationships, making ethical decisions, cyber-attack risks, data quality issues and liability issues in the event of problems. It is important to point out that these are only issues at the current stage. Naturally, AI is a technology that will continue to evolve in the future, and these issues will be resolved in the course of its evolution.
Status of AI adoption and percentage of Japanese companies using AI systems
According to the PwC Japan Group's annual AI forecast survey of Japanese and US companies, there was little difference in AI utilisation between Japan and the US in the 2022 survey, but the same survey in 2023 noted a divergence.
According to the company's survey, in Japan, around 50% of companies are using AI in their businesses, while in the US, the majority of companies are using AI, at over 70%. The difference is even starker when looking at companies that have not yet adopted AI, with a minority of 12% of companies in the US not yet adopting AI, compared to 35% of companies in Japan, with around a third of companies still in the study and demonstration phase.
On the other hand, IDC Japan's ‘Results of a Corporate User Survey on AI Systems in Japan in 2023’ points out that 72.4% of Japanese companies use AI systems, including those from PoC (proof of concept) in limited departments to company-wide use.
Although these surveys and others indicate that, globally speaking, Japanese companies are somewhat behind in their adoption of AI, the domestic AI system market shows that the full-scale use of AI is expanding in various industrial fields, including data analysis, business automation and application to customer service.
Various companies are actually achieving results from AI implementation.
So, which companies are actually adopting AI and how? Let us look at examples of AI adoption in various industries.
Firstly, the logistics industry, where long working hours are recognised as a social problem and efforts are being made to correct it in the name of reforming the way people work, has faced issues such as long working hours, overwork due to redelivery and refusal to receive deliveries, and increased workload on drivers due to lower loading rates. In order to correct these issues, AI has been introduced and is being promoted to solve these problems.
The introduction of AI has made it possible to improve the accuracy of forecasts of distribution volumes and peak timing by analysing large volumes of accumulated past data, realising optimisation of inventories through demand forecasts, optimising workforce shifts at distribution centres and optimising the allocation of truck transport personnel, thereby reducing manpower and improving efficiency. This has led to the correction of long working hours.
In addition to this, demonstration tests are underway for trucks on motorways using automated driving systems, which will enable automated planning of vehicle allocation under constrained conditions to improve the efficiency of the number of vehicles and routes.
IoT technology can also be used to connect things to the internet, so that products can be equipped with sensors and communication functions to check their condition and operation, and RFID tags can be used for product management to improve the efficiency of inspection work.
Let us look at another example of AI implementation in the manufacturing industry. In the manufacturing industry, AI is being introduced on a daily basis in areas such as visual inspection, abnormality detection and predictive maintenance. The manufacturing industry has been faced with a chronic labour shortage and ageing workforce due to a declining birthrate and ageing population, as well as a decline in the transfer of skills due to a shortage of young workers, and intensifying competition due to a shrinking population and globalisation. AI has been introduced to solve these challenges.
The introduction of AI has improved work efficiency, increased work safety, improved quality uniformity, reduced stress on employees, reduced the decline in performance due to employee fatigue, and reduced human accidents.
In addition to the logistics and manufacturing industries, this report introduces examples and trends in other major industries. We hope that this information will be useful in understanding the AI situation in each industry.
【Logistics industry】
Expectations for solving long-standing problems specific to the logistics industry, such as long working hours for personnel and low loading rates.
Company names for reference.
Fujitsu, Yamato Transport, Mitsui & Co.
The logistics industry is developing and introducing delivery management applications using AI technology that are effective in optimising delivery routes, loading rates and quality control during delivery. A vehicle dispatch system that automatically calculates the most suitable route by inputting data such as delivery address, time of day, weight and size of the parcel has already been developed and introduced by some logistics companies, enabling more efficient delivery and reduced transport costs.
In addition, some tracking systems have recently been developed and put into practical use, such as temperature control systems that utilise AI technology to prevent damage or loss of packages, while others provide real-time information on the status of package deliveries.
Examples include Suntory Logistics and Fujitsu, which have introduced AI judgment systems for forklifts; Yamato Transport, which uses AI to predict workload to realise efficient vehicle allocation and optimise the allocation of management resources; NEC, which uses AI and IoT to collect on-site data in real time; and Mitsui, which has introduced AI for abnormal detection to improve the quality of automatic box sealing Mitsui Global Logistics, which has improved the quality of its automated envelope
Efficient delivery and reduction of transport costs through optimisation of delivery routes and quality control during delivery.
▶Loogia, a service for optimising delivery routes.
Loogia’ (Optimind Co., Ltd.) optimises delivery routes and has been introduced by Japan Post, Sagawa Express and other companies. The AI system optimises delivery routes in order to optimise operations and reduce the shortage of drivers due to the increase in the volume of goods, and visualises events such as what routes delivery staff take and where they park.
【Retail industry】
Introducing AI to eliminate errors and lack of marketing due to product ordering.
Company names for reference.
Seven-Eleven, Ito-Yokado, Lawson, etc.
In the retail industry, applications are being developed in various fields, utilising AI, which is extremely capable in tasks such as data collection and analysis and automation. For example, AI has been introduced to automate stock management so that stock numbers can be adjusted to ensure optimum stock levels.
In addition, AI-based product recommendation systems have been introduced to cater to a wide variety of products and customer preferences, so that more appropriate products can be proposed to customers.
Other benefits include the ability to accurately understand customer needs and provide a better customer experience, as well as to develop and improve marketing strategies. The development of an efficiant retail industry is expected to continue in the future.
Examples of introductions include Seven-Eleven, which is aiming for manpower-saving convenience store facilities with an AI-based system for automatically calculating the number of orders, Lawson, which has established the Lawson Open Innovation Lab and is conducting an AI convenience store demonstration, and Itoyokado, which is using an AI-based product ordering system to predict the optimum number of products to be sold. Ito-Yokado, which uses an AI-based product ordering system to predict the optimum number of products to be sold.
It is aiming to create next-generation shops by eliminating problems such as product ordering errors and stock disposal.
▶An AI system that uses OCR technology to read product labels in batches.
Automagi Corporation has developed an AI system that uses a smartphone to read information on product labels in batches.
The system does not require prior detailed settings for each label and uses AI's OCR technology to enable batch reading by simply photographing the label. The system is expected to improve operational efficiency by enabling batch reading and management.
【Manufacturing industry】
Introduction is being promoted to resolve issues such as labour shortages, ageing employees and increased competition.
Names of companies for reference.
Yokogawa Electric, Skydisk, Toshiba, etc.
In recent years, the manufacturing industry has had to introduce new technologies to maintain its own competitiveness in terms of quality, cost, speed and flexibility, as price competition has intensified with globalisation. The introduction of AI is being promoted in order to upgrade production processes, improve quality, reduce costs and improve production efficiency.
It improves the autonomy of the production site, the machines themselves learn and evolve on the production site, process large amounts of data, and predict and improve problems in the production process and quality control. As a result, AI, which can realise improvements in quality and production volume, has a high affinity with the manufacturing industry and is expected to prevent unexplained accidents and problems, improve production efficiency, etc., and reduce costs. In the future, as the technology for utilising AI evolves, more advanced production systems will be realised.
Examples of introductions include Yokogawa Electric autonomously controlling chemical plants, Skydisk scoring casting conditions, Toshiba identifying defect factors based on sampling data, and Toyota automating magnetic flaw inspection.
Highly effective in reducing the decline in performance due to employee fatigue and reducing the number of human accidents, which should be avoided most.
▶ Use of AI in industrial robots.
Ascent Robotics Corporation is developing control software that can use a camera to recognise objects placed in pieces, automatically determine how to grab them and operate them. Industrial robots include robots that stack parts and other objects in pieces, and there are many products and solutions that utilise AI. The company's direction is to strengthen its services for logistics sites in the future.
▶ Automatic reading of instruments by a camera with built-in AI.
IntegrAI Inc. is working on a system that automatically converts all kinds of information, including numerical values indicated by manufacturing equipment, into data using a camera with built-in AI. The system is expected to contribute to reforms in the way manufacturing companies work by automating tasks that were previously checked visually by human operators.
【Food and beverage industry】
Promoting the introduction of AI with the aim of reducing the burden on employees and resolving manpower shortages.
Company names for reference.
Starbucks, Domino's Pizza, Fukushin, etc.
In the food and beverage industry, the introduction of AI applications is also expected to bring many benefits, including optimisation of shop operations, optimal preparation of foodstuffs, and improved marketing strategies.
One specific example of an introduction is Starbucks' effective sales promotion measures, such as the introduction of a function that recommends drinks and desserts to be served based on user preferences through its own app. Domino's Pizza has also successfully introduced an AI app in its delivery operations to calculate the best routes and reduce delivery times.
On the other hand, there are some challenges in introducing AI apps, such as high implementation costs and lack of technology for analysing data. It is therefore important to develop an appropriate implementation plan for the use of AI apps.
Some companies have shortened delivery times, reduced labour costs and reduced the burden of inventory work.
In addition to the aforementioned Starbucks and Domino's Pizza, other companies that have introduced AI applications include Rise Will, which has reduced labour costs by using AI cameras to visualise human flow, and Fukushin, which has reduced the burden of inventory work by using AI automated ordering.
【Nursing care industry】
The goal is to resolve issues such as manpower shortages, physical strain and interpersonal relationships with users.
Names of companies that can be used as references
A.I. Viewlife, Fujisoft Ltd. etc.
The introduction of AI in the care industry is expected to reduce the burden on carers and enable higher quality care for the elderly and disabled.
Specifically, functions that monitor the condition of the elderly and disabled and automatically notify them of their condition, detect and warn of medication side effects, and robots for walking assistance are being developed. Apps are also being developed that also use smartphones and tablets to support daily life, as well as technology to create a safe environment for the elderly and disabled.
Furthermore, there is the potential for AI to provide higher-quality care services by supporting the work of staff in care settings and taking on some of the health consultation duties, but there are still many challenges in the care industry, where human intuition and judgement are required in many situations and communication is vital.
Various attempts continue to be made in the field, including the introduction of a balance between experienced care staff and AI so that they can complement each other.
Enables early prediction of changes in physical condition and reduces the psychological burden on employees.
▶ A.I. Viewlife
A.I. Viewlife is a nursing care monitoring robot developed by A.I. Viewlife Co. It realises ‘visualisation’ of the nursing care scene, and uses wide-angle IR sensors and AI to detect dangerous movements such as falling over, and movements that predict danger such as getting up, which can lead to the prevention of serious accidents.
As a result of the actual introduction of the system, it has been reported that the number of near-misses and nursing care accidents has been reduced to zero, the number of visits to residents in nursing homes has been reduced, and the stress of the night shift on the part of caregivers has been reduced.
▶ Palro model for elderly care facilities lll
FUJISOFT Ltd. has developed a communication robot for elderly care facilities called Parlo. The robot is used for recreational purposes, such as chatting, dancing and singing, and the company has indicated that it will be equipped with a function to watch over the elderly in the future.
【Medical industry】
Potential to improve human resource shortages and harsh working conditions.
Company names for reference.
Fukuoka Wajiro Hospital, Minato Clinic, etc.
In the medical industry, AI supports the frontline in various aspects such as diagnosis, treatment and data analysis. For example, AI makes it possible to efficiently analyse large amounts of medical data, which in turn enables early detection of diseases and optimisation of treatment methods, which is expected to improve the accuracy of medical care and at the same time reduce medical costs.
AI also plays an important role in the medical field; for example, surgical support robots and automation of medical products have been made possible by the introduction of AI. This is expected to improve the accuracy of surgery and increase the effectiveness of treatment.
Furthermore, devices for self-checks and health management apps facilitate personal health management. This is expected to enable the efficient collection of information on health management, leading to the prevention and early detection of diseases.
Reduced workload of healthcare workers and psychological burden can be realised.
Examples of introductions include the AI medical interview ‘Ubie’ by Fukuoka Wajiro Hospital, the cloud-based electronic medical record ‘CLIUS’ at Minato Clinic, and the use of the disease risk prediction AI service by Tokyo Midtown Clinic.
【Construction industry】
AI will change civil engineering design⁉Expect benefits for personnel recruitment and labour management
Reference company names
Araya Corporation, etc.
AI technology is also being used in the construction industry, with AI applications being developed to improve efficiency, quality and safety in the design, construction and installation of buildings and facilities.
Typical examples are AI applications in building design. The introduction of AI into the building design process has enabled faster and more accurate designs than previously possible. AI can also provide design assistance to improve the energy efficiency of buildings, for example by optimising lighting, air conditioning and acoustic equipment.
Another example is AI applications on construction sites. This involves the use of AI at construction sites to provide on-site work support, such as optimising construction plans, progress management and the prediction and prevention of hazards. Specifically, drones can be used to acquire detailed survey data of buildings, and construction sites can be reproduced using building simulation software to improve building safety and efficiency.
The introduction of these AI apps is expected to reduce the time, financial and energy costs of the entire construction process and increase the quality and safety of buildings.
Reduced costs in the construction process, increased building quality and safety.
▶ Autonomous working robots.
Autonomous robots, which are unmanned construction machines operated by humans, are already active on many construction sites; AI-equipped construction machines include heavy machinery, excavators and bulldozers, which replace human work in their specific tasks. Work on construction sites requires more flexible autonomy than, for example, manufacturing robots in indoor environments, as environmental conditions may change and unexpected situations may arise.
▶ Site monitoring by drones.
AI-equipped drones that monitor construction sites from the sky to ensure site safety and prevent material theft are useful as security robots. High-resolution images of the site are read and video images are transmitted in real time to monitors on the ground or to the monitor's tablet. The work situation can be continuously monitored, so it can be used for on-site progress management and personnel allocation, thereby contributing to improved productivity.
【Education industry】
Breakthrough in the uncertainty of class progress due to teachers' long working hours and unforeseen circumstances.
Names of companies for reference.
Noda Juku, Eishinkan, Japan English Proficiency Test Association, etc.
In the education sector, AI applications have been developed to help support learning and improve the accuracy of assessment. First, AI apps related to learning support. These apps can analyse a learner's learning situation and provide personalised support, such as proposing a learning plan tailored to the learner's learning situation and providing feedback according to the learner's progress.
They provide effective learning support by analysing the learner's test-answering history, question-answering time, etc., and automatically determining their learning status. There are also apps that use speech recognition technology for English learning, for example, and are expected to help correct pronunciation.
AI-based assessment support applications are also attracting attention. They can collect the thinking and working processes of learners as they solve tasks, and provide a look-back function and areas for improvement in the task; AI-based automatic assessment systems are currently under development.
Curriculum structure and adaptive learning based on data analysis can be realised.
Examples of applications include Eishinkan, which uses data to predict the pass line for entrance examinations, Noda Juku, which analyses students' weak areas in real time, and the English Proficiency Test Association of Japan, which uses AI to automatically grade essay-type questions.
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