Policy Capacity for Novel Technology Adoption: Developmental Insights From Singapore's AI Adoption in Long-Term Care

Abstract

Worldwide, artificial intelligence-driven technologies, including robotics and autonomous systems (RAS), are adopted to address manpower shortages in long-term care. However, their effective use requires a reasonable degree of policy capacity across individual-, organisational- and system-levels. This research examines the strategies taken in Singapore to build these capacities on deploying novel technologies in long-term care and identifies key implementation challenges. Data were gathered via extensive semi-structured interviews involving 25 key informants, supplemented by secondary online sources, and analysed thematically. Findings revealed the presence of strong analytical and operational capacities in Singapore's adoption of RAS across different levels. Although organisational and system-level political capacities are evident, enhancing individual political capacity is needed to improve technology literacy and acceptance, especially among older citizens. To accelerate adoption, all three policy capacity domains must be leveraged: operational capacity to streamline management and implementation, analytical capacity to develop competencies and technical skills, and political capacity to mobilise support and promote user buy-in. These findings provide guidance for countries on how governmental and non-governmental actors can work effectively to enhance their policy capacity in novel technology adoption and realise them in phases, considering their level of development.