> **来源：[研报客](https://pc.yanbaoke.cn)** # Artificial Intelligence and the Labour Market in Japan # Artificial Intelligence and the Labour Market in Japan This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Member countries of the OECD. This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. # Please cite this publication as: OECD (2025), Artificial Intelligence and the Labour Market in Japan, OECD Publishing, Paris, https://doi.org/10.1787/b825563e-en. ISBN 978-92-64-64403-8 (print) ISBN 978-92-64-47596-0 (PDF) ISBN 978-92-64-97076-2 (HTML) Photo credits: Cover © Gorodenkoff/Shutterstock.com. Corrigenda to OECD publications may be found at: https://www.oecd.org/en/publications/support/corrigenda.html. $\odot$ OECD 2025 # Attribution 4.0 International (CC BY 4.0) This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of this licence (https://creativecommons.org/licenses/by/4.0/). Attribution - you must cite the work. Translations - you must cite the original work, identify changes to the original and add the following text: In the event of any discrepancy between the original work and the translation, only the text of the original work should be considered valid. Adaptations - you must cite the original work and add the following text: This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed in this adaptation should not be reported as representing the official views of the OECD or of its Member countries. Third-party material – the licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement. You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work. Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shall be Paris (France). The number of arbitrators shall be one. # Foreword As the general-purpose technology of our time, Artificial Intelligence (AI) is expected to profoundly change all aspects of our life, including work. The technology is rapidly evolving and is increasingly making its way into the workplace, bringing promises of increased productivity and improvements in job quality, amongst others. The question is not so much whether AI should be used at work, but rather how, so that its benefits can be maximised, while managing some of the risks such as: automation, invasions of privacy, bias and discrimination, and increased work pressure and stress, to name just a few. The evidence suggests that policies and institutions matter to making a success of AI, including: training and social dialogue, but also clear and proportionate regulation. In this series of country reviews, the OECD analyses the impact AI is having on a country's labour market from an internationally comparative perspective and also takes stock of that country's policies and institutions, against the backdrop of the OECD AI Principles for trustworthy AI. These country reviews aim to help policymakers better understand the risks and opportunities and offer them a menu of options to help workers and employers make a success of AI, drawing on examples and best practice from across the OECD. In addition, by providing an in-depth analysis of a particular country, these reviews allow policymakers from across the OECD to draw lessons from the experience of a specific country to inform their own policies and institutions. # Acknowledgements This was prepared by Takahiro Toda from Skills and Future Readiness Division of the Directorate for Employment, Labour and Social Affairs under the supervision of Stijn Broecke (Senior Economist, Skills and Future Readiness Division) and Glenda Quintini (Head of the Skills and Future Readiness Division). Valuable comments were provided by relevant ministries and organisations in Japan, including the Cabinet Office, the Cabinet Secretariat, the Personal Information Protection Commission (PPC), the Ministry of Economy, Trade and Industry (METI), the Ministry of Internal Affairs and Communications (MIC), the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the Bank of Japan (BOJ), the Ministry of Health, Labour and Welfare (MHLW), and the Japan Institute for Labour Policy and Training (JILPT). The OECD Secretariat would like to thank the MHLW, JILPT), and the Panel Data Research Center at Keio University for their support in carrying out this project. Particular appreciation is extended to Mitsuji Amase, Yuko Watanabe, and Noboru Ogino, members of the JILPT Al Study Group, for conducting a large-scale survey on the impact of AI adoption in Japanese workplaces and for providing the author with valuable data and many insights. Additional thanks are due to Professor Isamu Yamamoto and Professor Akihito Shimazu of Keio University for providing valuable insights and suggestions. This report is published under the responsibility of the Secretary General of the OECD, with the financial assistance of the MHLW. The opinions expressed and arguments employed in this report do not necessarily reflect the views of JILPT or those of the OECD Member countries. # Table of contents # Foreword 3 # Acknowledgements 4 # Abbreviations and acronyms 11 # Executive summary 12 # 1 AI use in the Japanese workplace 14 In Brief 15 1.1. Introduction 17 1.2. Who are the workers most likely to use AI at work? 19 1.3.What are the barriers to the adoption of AI in the workplace? 38 Annex 1.A. AI use in the Japanese workplace: Additional figures 43 References 46 Notes 49 # 2 Reaping the benefits of AI for performance at work and job quality 51 In Brief 52 2.1. Previous studies on impact of AI on the performance at work and job quality 54 2.2. The impact of AI on performance at work and job quality in the Japanese labour market 58 2.3. Initiatives to enhance outcomes related to AI on performance at work and job quality 86 Annex 2.A. Reaping the benefits of AI for performance at work and job quality: Additional figures 98 References 108 Notes 111 # 3 Preparing for the impact of AI on job quantity and skills needs 113 In Brief 114 3.1. The impact of AI on Job quantity and skills needs: A review of the literature 116 3.2. New evidence on the impact of AI on job quantity and skills needs in the Japanese labour market 118 3.3. How might training and worker consultation influence job quantity and skill requirements? 135 Annex 3.A. Preparing for the impact of AI on job quantity and skills needs: Additional figures 140 References 143 Notes 145 # 4 Maximising the benefits of AI while ensuring the safety and trustworthiness of AI technologies in the workplace 146 In Brief 147 4.1. Challenges related to company-provided training and self-learning for working collaboratively with AI 149 4.2. Challenges related to worker consultation on the use of new technologies in the workplace 159 4.3. Challenges related to establishing internal rules or guidelines to ensure employees can use GEAI appropriately in their work 165 4.4. Challenges related to building employee trust in the safety and reliability of AI technologies used in the workplace 170 4.5. Recent regulatory and policy developments in Japan regarding the safety, reliability, and transparency of AI technologies 181 Annex 4.A. Maximising the benefits of AI while ensuring the safety and trustworthiness of AI technologies in the workplace: Additional figures 185 Annex 4.B. Japan's new AI Act 195 References 197 Notes 199 # FIGURES Figure 1.1. Compared to other countries, Japanese AI adopters are more likely to report being managed by AI or having no interaction with AI at work, and less likely to report managing workers who work with AI 20 Figure 1.2. The proportion of Japanese employees using AI at work is the lowest among countries surveyed 21 Figure 1.3. Many Japanese employees expect AI use in workplaces to increase in the future 22 Figure 1.4. While the proportion of Japanese employees using AI at work in the information and communications sector exceeds $20\%$ , there are significant disparities across other sectors 23 Figure 1.5. Japanese AI adopters across many industries report that the use of AI in their companies has expanded since May 2022 24 Figure 1.6. Japanese employees in larger companies are more likely to report using AI, similar to those in other countries 25 Figure 1.7. Japanese AI users in companies experiencing a mild labour shortage are more likely to report using AI 27 Figure 1.8. There are regional disparities in Japan, with employees in the South Kanto and Kinki regions being more likely to say they are using AI 28 Figure 1.9. Japanese AI users are more likely to be young and middle-aged, male and more educated than non-users, similar to those in other countries 29 Figure 1.10. Japanese AI users (particularly GEAI users) are more likely to be regular employees than non-users or non-adopters 30 Figure 1.11. Japanese employees with disabilities or those engaging in childcare or long-term care are more likely to use AI 31 Figure 1.12. Japanese employees who frequently handle data analysis or tasks required creativity or tasks in hazardous place or managing are more likely to use AI 33 Figure 1.13. Japanese Managers, Professionals and Technicians and associate professionals are more likely to use AI 36 Figure 1.14. Japanese Managers, Professionals, and Technicians and associate professionals are most likely to report the use of AI in their companies has expanded since May 2022 37 Figure 1.15. Compared to U.S. companies, Japanese companies are more likely to report that a shortage of Al-related talent is a barrier to AI adoption, which has become more pronounced since 2022 39 Figure 1.16. Compared to U.S. companies, Japanese companies are more likely to report that shortage of employees who can promote AI adoption in the company, using their workplace experience and basic AI knowledge, which has become more pronounced since 2022 Figure 1.17. The most common reasons Japanese people give for not using GEAI are "I don't know how to use it' and "I don't need it in my life' 41 Figure 1.18. The most common reasons Japanese full-time employees, employers, or executives give for not using GEAI are "Concerns about the accuracy of the answers' content" and "No specific reasons" 42 Figure 2.1. Although Japanese AI users report that AI improves their performance and working conditions, the effects are more moderate compared to those in other countries 59 Figure 2.2. Japanese male AI users are less likely than their counterparts in other countries to report that AI improves their performance and working conditions 61 Figure 2.3. Japanese AI users with university degree are less likely than their counterparts in other countries to report that AI improves their performance and working conditions 62 Figure 2.4. Middle-aged and older Japanese AI users are less likely than their counterparts in other countries to report that AI improves their performance and working conditions 63 Figure 2.5. Japanese AI users in non-regular employment are less likely to report that AI improves their performance and working conditions 64 Figure 2.6. Japanese AI users in SMEs are more likely to report that AI improves their performance and working conditions 65 Figure 2.7. SMEs in all countries see enhanced performance as the main benefit of generative AI 66 Figure 2.8. SMEs in Japan are most likely to say that generative AI helps compensate for labour and skill shortages 67 Figure 2.9. Japanese AI users with disabilities or those engaging in childcare and/or long-term care are more likely to report that AI improves their performance and working conditions 69 Figure 2.10. The proportion of AI users reporting improvements in job quality, as well as the nature of these improvements, tends to vary by occupation 70 Figure 2.11. Although there are regional differences, Japanese AI users in rural areas as well as urban areas report that AI improves job performance and working conditions 71 Figure 2.12. Japanese AI users report that AI improves the work environment in various ways 73 Figure 2.13. Japanese AI users who frequently handle management tasks or tasks in hazardous places are more likely to report a higher improvement effect in job quality 74 Figure 2.14. Japanese AI users are more likely to report that AI improves their performance and working conditions if they experience changes in their tasks after using AI 76 Figure 2.15. As in other countries, more employees in Japan expect their wages to decrease rather than increase due to AI in the next 10 years, although the proportion of those expecting a decrease is lower than in other countries 77 Figure 2.16. GEAI users are more likely to report wage increases rather than decreases due to AI 78 Figure 2.17. AI users who are male, younger, regular employees, caregivers or have a disability are more likely to report wage increases rather than decreases after using AI 79 Figure 2.18. Japanese AI users in SMEs are more likely to wage increases rather than decreases after using AI, compared to those in large companies 80 Figure 2.19. AI users of plant and machine operators, and assemblers are most likely to report wage increases rather than decreases after using AI 81 Figure 2.20. Japanese AI users, both in urban and rural areas, are more likely to report wage increases rather than decreases after using AI 82 Figure 2.21. While Japanese AI users report that AI has increased their pace and their control over the sequence in which they perform their tasks, the impact is milder than other countries 83 Figure 2.22. While Japanese AI users report that it assists with decision making, the impact is milder than other countries 84 Figure 2.23. Japanese AI users also agree that AI helps them make better and faster decisions 85 Figure 2.24. The gap in reported improvements in job quality between Japanese AI users who received company-provided training and those who did not is greater than that in other countries 87 Figure 2.25. Japanese companies are more likely to provide in-house training seminars 88 Figure 2.26. Japanese AI users report that OJT or seminars at external organisations have the potential to be even more likely to improve their job performance 89 Figure 2.27. Japanese AI users who have received company training and engaged self-learning are even more likely to report positive outcomes of AI on job performance and working conditions 90 Figure 2.28. Although Japanese AI users who have received company training and engaged in self-learning report improvements in the work environment, caution is needed regarding the potential for increased overtime 91 Figure 2.29. Japanese AI users who have received company training and engaged in self-learning are more likely to report wage increases rather than decreases after using AI 92 Figure 2.30. Japanese AI users report that consultations help alleviate worries, enhance the efficiency of technology introduction, and clarify required skills 93 Figure 2.31. The differences in reported improvements in performance and working conditions between Japanese AI users who receive consultation and those who don't are larger than in other countries 94 Figure 2.32. Japanese GEAI users whose companies have established internal rules or guidelines are more likely to report positive outcomes of AI on job performance and working conditions 95 Figure 2.33. Japanese AI users trusting own company to only use AI that is safe and trustworthy are even more likely to report positive outcomes of AI on job performance and working conditions 97 Figure 3.1. Japanese Al adopters are less likely than those in other countries to know of individuals in their company who have lost jobs due to Al 119 Figure 3.2. Japanese AI users are the most worried about losing their job due to AI in the next 10 years 120 Figure 3.3. Japanese AI users are more likely to believe AI will result in job creation than job loss, whereas other employees hold the opposite view 121 Figure 3.4. The balance between worries about job loss and expectations of job creation from AI varies depending on the characteristics of Japanese AI users 122 Figure 3.5. AI users in Japan, regardless of company size, tend to report more expectations for job creation than worries about job loss 123 Figure 3.6. Japanese AI users in Managers and Professionals are more likely to report higher expectations for job creation than worries about job loss 125 Figure 3.7. The balance between the proportion of AI users reporting worries about job loss and those expressing expectations for job creation varies across regions in Japan 128 Figure 3.8. While Japanese AI users also report task automation and creation due to AI, the impact is milder than other countries 129 Figure 3.9. Particularly, Japan may be lagging behind other surveyed countries in automating repetitive and complex tasks 131 Figure 3.10. Japanese AI users, similar to their counterparts in other countries, tend to agree more with the idea that AI complements their skills rather than rendering them obsolete 132 Figure 3.11. $89.4\%$ of AI users in Japan reported that they expect the skills and abilities required in their current job to change due to AI over the next ten years 133 Figure 3.12. Japanese AI users in Managers, Professionals, Technicians and associate professionals are more likely to report that AI will change the skills or abilities required for their current job in the future 134 Figure 3.13. Japanese AI adopters anticipate that various skills will grow in importance over the next decade, particularly the ability to identify and resolve issues, adaptability to change, and ethics and compliance awareness 135 Figure 3.14. Japanese AI users who have participated in both company-provided training and self-directed learning are more likely to anticipate both job creation outweighing job loss and substantial changes in skill requirements in their current occupation over the next ten years 137 Figure 3.15. Japanese AI users whose employers consult them regarding the use of new technologies in the workplace are more likely to anticipate both job creation outweighing job loss and substantial changes in skill requirements in their current occupation over the next ten years 138 Figure 4.1. Although around $30\%$ of Japanese AI users report that their company has provided or funded training so that they can work with AI, this percentage is lower than in other countries 150 Figure 4.2. AI users in Japan are less likely to receive company training to work with AI 151 Figure 4.3. The difference between Japan and the average of 7 OECD countries in the proportion of AI users who received company training is greater for males than for females 152 Figure 4.4. The difference between Japan and the average of 7 OECD countries in the proportion of AI users who received company training is greater for middle-aged and older users than for younger users 153 Figure 4.5. $35\%$ of AI users in Japan report that they engaged in reskilling/upskilling to work with AI 154 Figure 4.6. $55\%$ of Japanese AI users who report that they engaged in reskilling/upskilling in 2023 had part of their training course fees subsidised 155 Figure 4.7. Older and non-regular Japanese employees are less likely to report using the Educational Training Benefits for reskilling or upskilling to work with AI 156 Figure 4.8. There are regional differences among Japanese AI users in whether they have access to resources for learning how to work with AI 158 Figure 4.9. Japanese AI users in companies facing labour shortage are less likely to report having the resources to learn to work with AI 159 Figure 4.10. Japanese employees and AI users are less likely than those in other countries to report that their employers consult workers or worker representatives regarding the use of new technologies in the workplace 160 Figure 4.11. The difference between Japan and the average of 7 OECD countries in the proportion of AI users whose employers consult them is greater for males than for females 161 Figure 4.12. The difference between Japan and the average of 7 OECD countries in the proportion of AI users whose employers consult them is greater for middle-aged users 162 Figure 4.13. AI users who middle-aged and older, non-regular employees are less likely to report that their employers consult them regarding the use of new technologies 163 Figure 4.14. Many Japanese employers who didn't consult employees on introducing new technology in the workplace saw it as an insignificant decision or a management decision 165 Figure 4.15. $34.8\%$ of generative AI users in Japan report that internal rules or guidelines have been established to support working appropriately with AI 167 Figure 4.16. SMEs using generative AI in Germany are the most likely to have guidelines in place 168 Figure 4.17. A certain percentage of GEAI users report that they don't understand or comply with company rules or guidelines to work appropriately with GEAI 169 Figure 4.18. Japanese employees are more likely to prioritise improving the safety, reliability, and transparency of AI technology as initiatives to reap its benefits and mitigate its negative impacts 170 Figure 4.19. Japanese AI users are less likely than those in other countries to explicitly report trusting their company to use only safe and trustworthy AI 171 Annex Figure 1.A.1. Many Japanese companies also expect Al-based digital technology to help address labour shortages 43 Annex Figure 1.A.2. Many Japanese SMEs cite the lack of the right skills among employees as a barrier to the use of GEAI in the workplace 45 Annex Figure 1.A.3. In every age group, a large number of Japanese employees use GEAI for drafting documents or texts 45 Annex Figure 2.A.1. Japanese GEAI users are more likely to report that AI improves their performance and working conditions compared to Japanese AI users who don't use GEAI 98 Annex Figure 2.A.2. Japanese AI users in manufacturing are the second most likely to expect wages in their sector to increase due to AI in next 10 years 102 Annex Figure 2.A.3. The average proportion of AI users reporting "No effect" across six tasks varies depending on the occupation 106 Annex Figure 3.A.1. Japanese AI users trusting own company to only use AI that is safe and trustworthy are more likely to anticipate both job creation outweighing job loss and substantial changes in skill requirements in their current occupation over the next ten years 142 Annex Figure 4.A.1. Among the other countries, Japanese AI users are the least likely to report that their company has provided or funded training so that they can work with AI 185 Annex Figure 4.A.2. Among surveyed countries, Japanese AI users are the least likely to report that their employers consult workers or worker representatives regarding the use of new technologies in the workplace 187 Annex Figure 4.A.3. Japanese AI non-users are less likely than those in other countries to explicitly report trusting their company to use only safe and trustworthy AI 193 Annex Figure 4.A.4. The smaller the company, the less likely Japanese employees are to report trusting their company to use only safe and trustworthy AI 194 # TABLES Annex Table 1.A.1. The relationship between AI usage rates and worker characteristics 44 Annex Table 2.A.1. Marginal effects of non-regular employment on job performance (Generalised Ordered Logit Model) 98 Annex Table 2.A.2. Marginal effects of company size on job performance (Generalised Ordered Logit Model) 99 Annex Table 2.A.3. Marginal effects of disability on job performance (Generalised Ordered Logit Model) 99 Annex Table 2.A.4. Marginal effects of caregiving responsibility on job performance (Generalised Ordered Logit Model) 100 Annex Table 2.A.5. Marginal effects of occupation on job performance (Generalised Ordered Logit Model) 101 Annex Table 2.A.6. Marginal effects of AI user attributes on wage (Generalised Ordered Logit Model) 103 Annex Table 2.A.7. Marginal effects of disability on wage (Generalised Ordered Logit Model) 103 Annex Table 2.A.8. Marginal effects of caregiving responsibility on wage (Generalised Ordered Logit Model) 104 Annex Table 2.A.9. Marginal effects of occupation on wage (Generalised Ordered Logit Model) 105 Annex Table 2.A.10. Marginal effects of training on job performance (Generalised Ordered Logit Model) 106 Annex Table 2.A.11. Marginal effects of worker consultation on job performance (Generalised Ordered Logit Model) 107 Annex Table 3.A.1. Japanese employees' expectations of Al's impact on job quantity over the next ten years (ISCO digit 3) 140 Annex Table 4.A.1. Marginal effects of residential area on the availability of resources to learn to work with AI (Generalised Ordered Logit Model) 185 Annex Table 4.A.2. Marginal effects of manpower status on the availability of resources to learn to work with AI (Generalised Ordered Logit Model) 186 Annex Table 4.A.3. Marginal effects of Japanese worker attributes on the likelihood of trusting or not trusting that their employer uses only safe and trustworthy AI (Generalised Ordered Logit Model) 188 Annex Table 4.A.4. Marginal effects of Japanese AI users attributes on the likelihood of trusting or not trusting that their employer uses only safe and trustworthy AI (Generalised Ordered Logit Model) 191 # Abbreviations and acronyms <table><tr><td>AI</td><td>Artificial intelligence</td></tr><tr><td>AI adopters</td><td>Employees whose companies use AI</td></tr><tr><td>ALMPs</td><td>Active Labour Market Policies</td></tr><tr><td>AISI</td><td>AI Safety Institute</td></tr><tr><td>AI users</td><td>Employees among AI adopters who have some interaction with AI at work</td></tr><tr><td>APPI</td><td>The Act on the Protection of Personal Information</td></tr><tr><td>ChatGPT</td><td>Chat Generative Pre-trained Transformer</td></tr><tr><td>ETB</td><td>Educational Training Benefits</td></tr><tr><td>GEAI</td><td>Generative artificial intelligence</td></tr><tr><td>HRDS</td><td>Human Resources Development Subsidies</td></tr><tr><td>IICP</td><td>Institute for Information and Communications Policy</td></tr><tr><td>IPA</td><td>Information-technology Promotion Agency, Japan</td></tr><tr><td>ISCO</td><td>International Standard Classification of Occupations</td></tr><tr><td>JDLA</td><td>the Japan Deep Learning Association</td></tr><tr><td>JILPT</td><td>Japanese Institute for Labour Policy and Training</td></tr><tr><td>JNIOSH</td><td>National Institute of Occupational Safety and Health, Japan</td></tr><tr><td>JPY</td><td>Japanese Yen</td></tr><tr><td>LLM</td><td>Large Language Model</td></tr><tr><td>METI</td><td>Japanese Ministry of Economy, Trade and Industry</td></tr><tr><td>MEXT</td><td>Japanese Ministry of Education, Culture, Sports, Science and Technology</td></tr><tr><td>MHLW</td><td>Japanese Ministry of Health, Labour and Welfare</td></tr><tr><td>MIC</td><td>Japanese Ministry of Internal Affairs and Communications</td></tr><tr><td>OECD</td><td>Organisation for Economic Co-operation and Development</td></tr><tr><td>OFF-JT</td><td>off-the-job training</td></tr><tr><td>OJT</td><td>on-the-job training</td></tr><tr><td>PES</td><td>Public Employment Services</td></tr><tr><td>PIAAC</td><td>OECD's Programme for the International Assessment of Adult Competencies (Survey of Adult Skills)</td></tr><tr><td>PPC</td><td>Japanese Personal Information Protection Commission</td></tr><tr><td>RCVADP</td><td>The Regional Consortium for Vocational Abilities Development Promotion</td></tr><tr><td>RPA</td><td>Robotic Process Automation</td></tr></table> # Executive summary Japan faces serious shortages of labour and skills due to a declining birth rate and an ageing population and therefore aims to achieve economic growth and sustained wage increases by improving the productivity and working environment of each and every worker. While AI alone cannot achieve these goals, the analysis in this report indicates that AI can be part of the solution. Indeed, workers in Japan tend to be very positive about the impact of AI on their job performance, working conditions and wages, and it seems AI could also help address labour shortages, complement worker skills, and support decision making. AI users in Japan are also more likely to expect that AI will lead to job creation than job loss. These positive effects of AI are widely distributed across Japanese workers, including those in small and medium-sized enterprises (SMEs), rural companies, persons with disabilities, and workers balancing work with childcare and/or long-term care responsibilities. However, Japanese AI users tend to perceive these improvements more modestly than in other countries. In addition, some groups of workers – such as older workers and non-regular employees – appear less likely to benefit. This report identifies three areas in which Japan appears to be falling behind other countries: (i) the rate of AI use at work; (ii) the extent to which AI improves job performance and working conditions; and (iii) the implementation of initiatives which are associated with better outcomes for workers, such as: company training and self-learning, worker consultation, guidelines for the use of AI at work, and measures to ensure the safe and trustworthy use of AI at work. Across all industries, only $8.4\%$ of workers in Japan report using AI in the workplace and, on average, $35.8\%$ of AI users say it has improved their job performance or working conditions – highlighting the need for Japan to simultaneously reduce barriers to AI adoption and promote measures that enhance the outcomes of AI for workers. In addition, Japan should ensure that no workers are left behind. Non-regular workers and older workers in particular are less likely to use AI at work, less likely to benefit from AI use, and also less likely to benefit from measures such as training and worker consultation. Improving older workers' use of AI and ensuring they benefit from AI use at work is especially important in the context of Japan's rapidly ageing society. To maximise Al's benefits and mitigate its risks, the OECD recommends that policymakers in Japan: - Strengthen initiatives that enable companies to scale up the provision of training, including through financial support, to help employees work effectively with AI. The Japanese Ministry of Health, Labour and Welfare (MHLW) already provides subsidies for Al-related company training through the Human Resources Development Subsidies, but enhancing the accessibility of these subsidies could encourage more companies to implement training programmes. This report reveals regional disparities in the proportion of Japanese AI users who have access to resources for learning to work with AI. If companies are considering providing financial assistance to support employees' studies at universities or other educational and training institutions or are outsourcing off-the-job training (Off-JT) related to AI, relevant resources within the region need to be made available. The Regional Consortium for Vocational Abilities Development Promotion, established in each prefecture of Japan, have the potential to serve as effective platforms through which stakeholders and relevant organisations can collaborate to expand the range of Off-JT related to AI, as well as the financial support that companies can provide to their employees for training to work effectively with AI, and in alignment with the needs of local businesses. - Strengthen initiatives for workers to engage in self-directed learning to work effectively with AI. The Educational Training Benefits (ETB) has played an important role in supporting a wide range of workers in reskilling or upskilling to work with AI. However, among AI users in Japan who undertook reskilling or upskilling, only $55\%$ used the ETB, indicating substantial room for further uptake. The ETB should also continue to expand the number of online courses – while ensuring the quality and effectiveness of training – in order to reduce regional disparities. - Foster worker consultation on the adoption of new technologies at work. It is important for MHLW to raise awareness – using concrete examples and evidence – of the value of such worker consultation, which can deliver mutually beneficial outcomes for workers and employers, including in terms of job performance and working conditions. - Encourage companies to establish guidelines for the appropriate use of generative AI (GEAI) in the workplace and ensure employees both understand and comply with such guidelines. The Japan Deep Learning Association (JDLA) has developed model guidelines for the use of GEAI, freely available to all on its website. Japanese companies should actively use these resources to develop guidelines tailored to their operational contexts. Moreover, it is important for companies to ensure that employees fully understand and comply with such guidelines. - Support employers in building employee trust in addressing the risks associated with AI. The MHLW should compile good practices from companies that have successfully managed to reap the benefits of AI while also addressing the associated risks and disseminate such information – together with relevant data and evidence – in a manner that is easily accessible to a wide audience. Subsequently, policymakers could consider developing guidelines to support both employers and workers in addressing the benefits and risks associated with AI use in the workplace. - Strengthen active labour market policies (ALMPs) to support workers through the transition. MHLW should enhance the matching functions of the local Public Employment Service (known as Hello Work in Japan) and provide vocational training for individuals who have been displaced due to AI. The use of AI at Hello Work should be promoted to improve job-matching and the working conditions of staff. Some workers may face difficulties in moving to higher-skilled occupations or in relocating to other regions. In the future, it may be useful to consider support measures that create new employment opportunities in fields where jobseekers can make the most of their existing human capital, in order to prevent declines in their wages or working conditions. - Lower the barriers to AI adoption. When introducing AI, key challenges include: a shortage of personnel who can help the company introduce AI using their basic AI knowledge and workplace experience; a lack of employee skills to integrate AI into existing services and products; a shortage of AI developers; and concerns about AI-related risks such as safety, trustworthiness, and transparency. Japan should advance its efforts under the new AI Act, which aims to both promote AI research, development, and use, and address AI-related risks. - Promote diverse career pathways, including job-based specialist roles with high autonomy. Al-related improvements in job performance, working conditions, and wages are more frequently reported in high-skilled occupations, particularly professional roles. However, Japan's workforce development system has traditionally focussed on producing generalist workers without specific areas of expertise. Moreover, seniority-based promotion systems tend to foster hierarchical organisational structures, and the limited autonomy of workers may make it more difficult for them to recognise the benefits of AI. Therefore, it is important to promote awareness of the Job-Based Personnel Management Guidelines, which were jointly issued by the Cabinet Secretariat, the Ministry of Economy, Trade and Industry (METI), and the MHLW, as they provide practical examples to support companies in advancing job-based human resource management. # 1 AI use in the Japanese workplace This chapter explores the characteristics of workers using AI in Japanese workplaces. The proportion of AI users in Japan is lower than in other countries, highlighting significant potential for future growth and the need to promote the safe and trustworthy integration of AI in the workplace. Ensuring inclusive access to AI in the workplace is also essential. Men and older workers, those without a university degree, employees of smaller companies, non-regular workers, those in the Medical, healthcare and welfare sector, and workers in low-skilled occupations (Plant and machine operators, assemblers, and Elementary occupations) are less likely to use AI at work. In contrast, employees with disabilities, those managing childcare and/or long-term care responsibilities, high-income workers, those in the Information and communications sector, the Finance and insurance sector, the Scientific research, professional and technical services sector, workers in high-skilled occupations (Managers and Professionals), and those in companies experiencing mild labour shortages are more likely to use AI at work. In parallel, Japanese companies struggle with a lack of talent with the necessary workplace experience and basic AI knowledge to adopt AI in the workplace. Japan must strengthen its efforts to develop and secure such talent. Furthermore, from the perspective of employees, ensuring the accuracy, safety, and reliability of AI remains a crucial issue for promoting broader adoption. # In Brief This chapter explores the characteristics of AI users in Japanese workplaces. The share of Japanese workers who say they use AI at work is lower than in other countries, and there are disparities in its use. For Japan to fully harness the benefits of AI, it should ensure that more Japanese workers can access safe and trustworthy AI, while also addressing disparities in use of AI. - $8.4\%$ of employees in Japan say they use AI at work, and $6.4\%$ use GEAI. Focusing on the finance and insurance and manufacturing sectors only, the proportion of AI users in Japan is the lowest among the countries for which comparable data is available. This suggests that Japan has significant room growing the use of AI in the workplace. - Many employees already view AI as a megatrend shaping the future of work, although perceptions of the extent to which its use will grow vary among workers. $93.0\%$ of Japanese AI users, $82.4\%$ of Japanese AI non-users (among AI adopters), and $50.7\%$ of Japanese AI non-adopters anticipate that the use of AI in the workplace will increase over the next ten years. - There are significant disparities in the proportion of Japanese employees using AI at work by industry sector. The difference between the sectors with the highest and lowest use is 18.8 percentage points (p.p.): $22.9\%$ in the Information and communications sector and $4.1\%$ in the Accommodations, eating, and drinking services sector. Econometric analysis reveals that, compared to workers in Accommodations, eating and drinking services, those in Agriculture, forestry and fisheries, Manufacturing, Information and communications, Transport and postal services, Wholesale and retail trade, Finance and insurance, and Scientific research, professional and technical services, are more likely to use AI at work. In contrast, workers in Medical, healthcare and welfare are less likely to report using AI in their jobs. Significant disparities also emerge in the proportion of Japanese employees using AI at work by company size, similar to those observed in other countries surveyed. The difference in AI use at work between companies with up to 19 workers and those with 10 000 or more workers is 16.9 p.p. - According to the Bank of Japan's Tankan for June 2025, Japanese companies are most likely to report labour shortages in the Construction and Accommodation and food services sector. AI has the potential to address labour shortages in various ways, such as through the automation of routine tasks or the standardisation of complex tasks. Employees in Japanese companies experiencing moderate labour shortages make greater use of AI than those in companies with an appropriate level of staffing. However, this trend is not observed among employees in companies facing severe labour shortages. It is not possible to determine causality, however. It may be the case that companies experiencing moderate shortages had previously experienced severe shortages, but that AI has helped them address these shortages. Alternatively, it could indicate that once companies face severe labour shortages, introducing AI becomes more challenging. Disparities also emerge in the proportion of Japanese employees using AI at work by region. The difference between the highest proportion in Tokyo (13.8%) and the lowest in Shimane (2.5%) is 11.3 p.p. While these differences are largely thought to arise from variations in the characteristics of companies across regions, an econometric analysis controlling for several individual attributes also shows that the rate of AI use is significantly higher in South Kanto (including Tokyo) compared to other regions. - Japanese AI users in the finance and insurance and manufacturing sectors are more likely to be young or middle-aged, male and more highly educated than non-users, similar to AI users in other countries. Based on an econometric analysis covering all industries and controlling for several individual attributes, Japanese AI users are more likely to be regular employees, have higher incomes, and work longer hours. Employees with disabilities or those balancing childcare and/or long-term care responsibilities are more likely to use AI at work than their counterparts without such responsibilities. Since the employees with disabilities referred to in these findings are limited to those who participated in the JILPT web survey, caution is needed in generalising this finding to all employees with disabilities. However, these it suggests that AI could be used more extensively to support individuals with disabilities and those seeking to balance their work with caregiving responsibilities. - AI usage is higher among employees engaged in tasks such as analysing data and information, solving problems using creativity, and managing and motivating teams, while it is lower for those doing routine and repetitive tasks as well as physical tasks. This suggests a higher use among workers who do cognitive tasks and is in line with the finding that physical and repetitive tasks have not so much been automated as delegated to non-regular workers. - Managers, Professionals, Technicians, and associate professionals are among the most frequent AI users, while Plant and machine operators, assemblers and workers in Elementary occupations are less likely to use AI at work. The difference between the occupations with the highest and lowest use is 13.5 p.p. A more detailed classification based on ISCO's DIGIT3 shows that occupations with the highest AI usage include: ICT service managers, Administration professionals, and Finance professionals, while those with the lowest usage include Domestic, hotel and office cleaners and helpers, Personal care workers in health services, and Manufacturing labourers. This chapter also explores the barriers to implementing AI in the workplace, reflecting both the challenges faced by companies attempting to adopt AI and the hesitation of workers to use it. - The Japanese Government has outlined plans to develop a total of 2.3 million "Human resources for advancing digital technology implementation" between FY2 022 and FY2 026. However, Japanese companies are struggling more than their U.S. counterparts with a shortage of AI-related talent, with the most pressing challenge being a lack of employees capable of promoting AI adoption using their workplace experience and basic AI knowledge. Other issues companies face include: a lack of information about the benefits of AI use, insufficient examples from other companies, difficulties related to the data required for AI training, concerns around costs, and a shortage of AI products and services that are easy for companies to adopt. A recent OECD survey of SMEs reveals that Japanese SMEs are significantly more likely than their counterparts in other countries to cite a lack of skills to use GEAI as a barrier to its adoption. Japanese SMEs are also concerned about AI-related risks, such as copyright, legal or regulatory issues associated with generative AI. - $27.6\%$ of Japanese employees do not have specific reasons for not using GEAI at work. Therefore, if effective methods for using GEAI in the workplace are established, there is a possibility that AI use could expand significantly in Japan. On the other hand, $84.4\%$ of those involved in the introduction of GEAI in the workplace at large companies expressed concerns about using GEAI, including: the accuracy, safety, and reliability of GEAI technologies, as well as the technical difficulty of integrating AI with existing systems. # 1.1. Introduction The OECD defines an AI system as "a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment (OECD, 2024[1])" AI can be seen as a General-Purpose Technology (GPT) (Brynolfsson, Rock and Syverson, 2017[2]). GPTs are characterised by their pervasiveness, inherent potential for technical improvements and innovative complementarities (Bresnahan and Trajtenberg, 1992[3]). AI has the potential to be pervasive, impacting a broad variety of sectors and occupations. Not only does it improve over time through the expertise of inventors or developers, but also by learning on its own from data and its past predictions. Furthermore, it has the capability to spawn complementary innovations. From the perspective of labour policy, the introduction of AI in the workplace is a key issue for the future of work. Japan, grappling with a severe labour shortage caused by a declining birthrate and an ageing population, has implemented measures to support workers who wish to remain in the workforce, change jobs, or find employment. In addition, Japan has aimed to foster diverse working environments and improve job quality by promoting work style reforms, such as addressing the culture of long working hours and eliminating unfair treatment disparities among workers. These initiatives are also intended to drive sustainable economic and wage growth by enhancing labour productivity through streamlined work tasks, optimised work processes, and increased capital investment. AI has the potential to further advance these policy efforts while aligning with the overall direction of Japan's labour policy so far. In other words, AI holds significant potential to enhance job performance and working conditions, assist workers in transitioning to more desirable jobs, and improve access to the labour market. At the same time, maximising the benefits of AI in the workplace requires comprehensive measures and preparations. First and foremost, it is critical to ensure that AI adoption does not exacerbate inequality, contribute to discriminatory practices, facilitate the misuse of surveillance technologies, or infringe upon workers' privacy. To achieve this, it is essential not only to enhance the safety and reliability of AI technology itself but also to conduct worker consultations during its introduction. Additionally, establishing internal guidelines for employees on AI use can be an effective approach. These guidelines can serve as an ongoing communication tool between labour and management, facilitating discussions on the appropriate use of AI after implementation. They also enable a prompt response to any new issues that may arise post-implementation. Furthermore, AI integration in the workplace has the potential to reshape job quantity, work tasks, and the skill requirements for various occupations. Therefore, governments must take proactive steps to support workers in reskilling and upskilling to work with AI, as well as in making smooth transitions to new jobs that leverage their existing skills and experience, while making continuous efforts to appropriately understand the actual and potential changes occurring in the world of work. This report aims to evaluate the use of AI in Japanese workplaces from multiple perspectives and sets out recommendations for policymakers in Japan to support the development of human-centred workplaces empowered by ethical and trustworthy AI. This report primarily consists of findings from thorough analyses of microdata from two worker surveys: one conducted by the OECD (Lane, Williams and Broecke, 2023[4]) and the other by the Japanese Institute for Labour Policy and Training (JILPT) (JILPT, 2025[5]). Particularly, the latter survey is valuable as it was the first large-scale, all-industry survey conducted by JILPT, an independent administrative agency under the Min