Digital Transformation for an Ageing Nation: The MalaysiaAgeNet Socio-Technical Reference Architecture and Readiness Framework
DOI:
https://doi.org/10.70917/ijcisim-2026-4334Keywords:
Ageing society, digital inclusion, digital transformation, information systems architecture, Malaysia, responsible AIAbstract
Malaysia's demographic transition is occurring alongside rapid expansion of digital government, artificial intelligence (AI), digital health, and data-sharing infrastructure. Yet ageing-related initiatives remain vulnerable to fragmented applications, unequal access, weak interoperability, and technology-led scaling without evidence of public value. This study develops MalaysiaAgeNet, a socio-technical reference architecture and readiness framework for national digital ageing transformation. It uses a design-oriented secondary synthesis that re-analyses the authors' published scoping-review corpus of 63 global academic and policy sources and updates the Malaysian context with 12 Malaysian policy, legal, statistical, and administrative instruments and three recent empirical studies. Policy mechanisms were translated into system requirements, architectural layers, maturity anchors, service scenarios, and decision gates. The resulting architecture comprises five operational layers: (1) experience and access; (2) community delivery; (3) domain services; (4) service orchestration and interoperability; and (5) data, analytics, and responsible AI. Two cross-cutting planes provide trust, assurance, observability, and continuous learning. A proposed five-level (0–4) maturity model assesses mission and governance, inclusive delivery, interoperable infrastructure, trust and assurance, and outcome learning. Scenario walkthroughs show how assisted telehealth, care-plan continuity, smart-home alerts, benefit applications, and social participation can traverse the architecture while preserving human responsibility and non-digital alternatives. The framework aligns current Malaysian ageing, health, digital, data-sharing, and AI policies around shared implementation logic. It offers a testable design proposition rather than a validated national system; stakeholder validation, pilot deployment, and longitudinal evaluation remain necessary.