KaizenTalent: Towards an AI-Augmented, Culturally-Aligned Talent Management Framework for Japan's Ageing Society 5.0 Workforce

Japan's working-age population is shrinking faster than any other advanced economy's, and organisations are turning to AI-driven HR analytics to compensate. Most of these tools, however, were built for Western workplaces: individual performance metrics, top-down feedback, and fast managerial intervention. That logic does not map cleanly onto Japanese organisational norms, which run on Kaizen (small, continuous improvement), Nemawashi (building consensus quietly before a decision is announced), and seniority-based employment structures that Western attrition models were never designed to represent. This paper reviews four strands of literature -Japan's demographic outlook, machine-learning approaches to attrition prediction, the cultural mechanics of Kaizen and Nemawashi, and Japan's Society 5.0 policy for human-centred technology -to argue that a real gap exists: almost nobody designs talent-management systems around these norms rather than in spite of them. It then proposes KaizenTalent, a three-module conceptual framework -a Talent Risk Intelligence Module, a Kaizen-Aligned Development Pathway, and a Human-Centred Engagement Interface -intended to pair predictive analytics with an implementation logic that actually fits how Japanese organisations make decisions. The paper closes by specifying what would need to happen next: a pilot study, real organisational data, and a candid test of whether this approach outperforms the imported alternative it responds to.