PBESProceedings of Business and Economic Studies2209-26412209-265XBio-Byword Scientific Publishing Pty. Ltd.10.26689/pbes.v8i7.13109ArticleGenerative AI for Cost Reduction in Japanese Corporations: Cultural Insights and Deployment Frameworkhttps://artdesignp.com/journal/PBES/8/7/10.26689/pbes.v8i7.13109LuoJinshan2025872025-12-15Generative AI is becoming a central driver of corporate digital transformation, offering major potential for efficiency improvement and cost reduction. Japanese corporations, however, face cultural barriers, such as long-term orientation and group cohesion, while ensuring stability and quality, now create structural rigidities and higher costs. This study examines these cultural dimensions and their impact on technology adoption, proposing a macro-micro AI deployment framework aligned with Japan’s organizational context. At the micro level, agentic AI enhances employee autonomy and adaptability, mitigating procedural rigidity and improving productivity. At the macro level, large AI models integrate dispersed resources, reduce silos, and strengthen knowledge flows. Implementation involves creating internal communities of practice and redesigning incentives to promote cross-functional collaboration, supporting a shift from functional hierarchies to matrix-based teams. This study offers a culturally grounded roadmap for Japanese corporations, showing how generative AI can drive efficiency, sustainable cost reduction, and structural transformation while preserving core cultural strengths.

Information-Technology Promotion Agency, 2024, Japan DX Trend 2024: Survey on Digital Transformation Initiatives, Technology Utilization, and Human Resource Development in Japanese Enterprises.

ABeam Consulting Ltd, 2025, Survey on the Status of DX Initiatives in Japanese Companies.

Lincoln J, Lakkeberg A, 1993, Culture, Control and Commitment: A Study of Work Organization and Work Attitudes in the United States and Japan, CUP Archive.

Haitani K, 1990, The Paradox of Japan’s Groupism: Threat to Future Competitiveness? Asian Survey, 30(3): 237–250.

Kubota R, 2003, Critical Teaching of Japanese Culture, Japanese Language and Literature, 37(1): 67–87.

Matanle P, Matsui K, 2013, Lifetime Employment in 21st Century Japan: Stability and Resilience under Pressure in the Japanese Management System. Wirtschaftpsychologie, 2013(15): 15–44.

Schaede U, 2022, The Digital Transformation and Japan’s Political Economy, Cambridge University Press, Cambridge.

Eisfeldt A, Schubert G, Zhang M 2023, Generative AI and Firm Values, National Bureau of Economic Research.

Acharya D, Kuppan K, Divya B, 2025, Agentic AI: Autonomous Intelligence for Complex Goals: A Comprehensive Survey. IEEE Access, 2025.

Yao Y, Duan J, Xu K, et al., 2024, A Survey on Large Language Model (LLM) Security and Privacy: The Good, The Bad, and The Ugly. High-Confidence Computing, 4(2): 100211.

Bansal G, Nawal A, Chamola V, et al., 2024, Revolutionizing Visuals: The Role of Generative AI in Modern Image Generation. ACM Transactions on Multimedia Computing, Communications and Applications, 20(11): 1–22.