GUGA Updates One of Japan’s Largest Generative AI Use Case Databases With Cases Through March 2026

The Generative AI Utilization Promotion Association (GUGA), a general incorporated association working to implement generative AI in society and restructure industry, announced that it has updated its “Generative AI Use Case Database,” one of the largest of its kind in Japan, by adding cases through March 2026. An analysis of 472 cases from October 2025 to March 2026, including newly added entries, shows that generative AI adoption is moving beyond efficiency gains at the task level. Organizations are increasingly reviewing business processes, operating environments, and internal adoption structures on the assumption that people will collaborate with generative AI. Database URL: https://www.notion.so/guga2023/AI-25d568a8e68780889f86fa9cd8977eb8 The Generative AI Use Case Database collects and organizes generative AI use cases announced by companies and organizations in Japan. GUGA council members with AI expertise serve as “PICKERs,” reviewing each case individually and including only those confirmed to be highly reliable. The database is free for anyone to browse. Users can search by keyword and switch views by publication date, company, industry, and other categories to find cases that match their needs. The database aims to help users understand industry trends, gain hints for solving challenges according to each organization’s phase, and further promote generative AI adoption. With the latest update covering cases through March 2026, GUGA has released a “Generative AI Use Case Analysis Report” analyzing social changes and trends in Japan based on 472 cases from October 2025 to March 2026. The first major trend is that AI agent adoption is moving from verification to operational implementation. In the first half of fiscal 2025, from April to September, many initiatives were still at an early stage, such as hands-on events, proof-of-concepts, and concept announcements. In the latest period, however, more cases show AI agents being incorporated into specific workflows such as sales analysis, lending operations, financial accounting, development processes, and customer support. This indicates that AI agent use has shifted from experimentation to the question of which operations should adopt AI agents and how. Rather than being used merely as conversational tools, AI agents are increasingly taking on upstream work such as information gathering, organization, first-pass processing, and preparation of decision-making materials. The second trend is progress in building environments designed for collaboration with generative AI. During this period, there were more cases focused not simply on introducing generative AI, but on creating environments for safe and continuous use. Business-specific LLMs, on-premises environments, dedicated environments, safety evaluations, and governance design drew attention. Preparing usage environments and operating conditions for practical deployment has become increasingly important. These cases can be viewed not merely as efforts to strengthen the safety of individual services, but as foundation-building for using generative AI even in operations that require confidentiality, continuity, and manageability. Generative AI adoption is moving from asking whether it can be introduced to determining what environments allow stable, continued use. The third trend is that improvement in adoption maturity is moving from individual ingenuity to organizational systems. Generative AI use is no longer limited to voluntary efforts by individuals. Through training, internal study sessions, certification systems, and similar measures, it is becoming something organizations actively support. Across companies, universities, and local governments, the central issue is shifting from introduction itself to how to prepare people and operational foundations that enable continued use in the field. Generative AI adoption is moving from a stage in which “those who use it, use it” to a stage in which organizations expand, support, and embed it. Efforts to build foundations that include not only technology deployment but also talent development and adoption programs became more concrete during this period. The leading trend keywords for October 2025 to March 2026 were: AI agent, appearing in 64 cases, with more examples of incorporation into sales, lending, accounting, development, and customer support workflows; LLM, appearing in 37 cases, as use premised on practical deployment expands, including business-specific and Japanese domestic models, increasing the importance of platform selection; voice, appearing in 27 cases, with adoption expanding in call centers, meeting minutes, medical records, guidance operations, and other field-facing settings; talent development, appearing in 14 cases, with lectures, training, certification systems, and company-wide initiatives advancing adoption within organizations; and chatbot, appearing in 14 cases, especially in local government and public-sector implementations for resident guidance and inquiry handling. The analysis covered 472 cases from October 2025 to March 2026. Trend keywords were counted by exact match in each case summary field, with multiple appearances of the same word in the same case counted as one case. “AI” and “generative AI” were excluded. GUGA council members who served as PICKERs also provided comments on the cases from January to March 2026. Yuta Ibaraki, Representative Director of AndDot Inc., said the selected cases share a common sign: corporate AX, or AI Transformation, is entering full swing. Examples such as document automation and the redefinition of hiring policies by financial institutions and major IT vendors show a shift toward AI-first management. AX is also spreading in fields such as manufacturing, finance, and pharmaceuticals, where quality and safety are required, suggesting the maturation of AI reliability and governance structures. He expressed hope that the database will serve as a guide for organizations pursuing AX. Kazuhiro Saeki, AI Specialist in QTnet’s AI Business Division, said he mainly selected cases in the public, local government, telecommunications, and network fields. He noted that companies and institutions where generative AI adoption is spreading internally are developing a variety of initiatives. As workshops and courses for internal adoption are also increasing, he encouraged companies struggling to spread adoption to refer to successful examples from others. Kosuke Takagi, Executive Officer and Head of the AI Innovation Office at SALES ROBOTICS Corporation, selected cases across a wide range of industries, including consulting and professional services, travel and tourism, information and communications, healthcare, nursing care and pharmaceuticals, and entertainment. Although little time had passed since the previous update, many more cases had already emerged, making him feel that the shift toward AI across society is accelerating. He also observed an increase in inter-company collaboration and co-creation cases, with more examples combining the strengths of multiple companies. Hiroaki Tanaka, General Manager of the AI Solution Development Department at OPT Inc., mainly handled media, advertising, and publishing. Reviewing the cases showed that generative AI is being incorporated not only into content creation, but also into customer touchpoints such as search and inquiry response, as well as business processing, increasingly in connection with cloud and data infrastructure. He was particularly struck by the shift from PoC to real-world operation, with progress in redesigning operations around AI and in operational design that includes governance. Database overview: The Generative AI Use Case Database contains 1,551 cases as of March 31, 2026. It is compiled by collecting and reviewing press releases on generative AI use cases distributed by companies and organizations. The covered period is May 2024 to March 2026. Cases are classified into 19 industries: manufacturing; energy and infrastructure; construction and real estate; food and consumer goods; healthcare, nursing care and pharmaceuticals; finance and insurance; retail, distribution and trading companies; transportation and logistics; technology; telecommunications and networks; media, advertising and publishing; services; education; consulting and professional services; public sector and local government; sports; entertainment; travel and tourism; and others. The provider is GUGA, with planning and operational cooperation from AndDot Inc. The Generative AI Passport is one of Japan’s largest certification exams for preventing generative AI risks. It covers basic knowledge, trends, and usage methods related to generative AI, as well as points of caution such as information leakage and rights infringement, enabling AI beginners to systematically acquire the minimum literacy they need. Through this certification, GUGA aims to visualize companies and talent with the literacy required for safe generative AI use and promote standardization of AI literacy in Japanese society. About GUGA: GUGA is one of Japan’s leading generative AI platforms, aiming to restructure industry through the social implementation of generative AI. Its initiatives include providing the Generative AI Passport certification exam, holding the GenAI HR Awards 2025 to recognize outstanding practices in human capital strategy for the generative AI era, and offering the Generative AI Use Case Database, which collects generative AI use cases from companies and organizations in Japan. Together with government agencies and many other stakeholders, GUGA promotes the planning and provision of generative AI infrastructure needed to strengthen Japan’s future. The association was established on May 10, 2023, is located at THE PORTAL Ningyocho 7F, 2-25-15 Nihonbashi Ningyocho, Chuo-ku, Tokyo, and is represented by Chairman Satoshi Ibata. URL: https://guga.or.jp/