[Forum] AI-Driven Transformation in Elder Care: Industry Practices and Policy Initiatives in Focus
Amid the challenges of an aging society and care workforce shortages, AI is emerging not merely as a tool for efficiency but as a catalyst for personalized, predictive, and collaborative care. (Source: Fotor AI)
As the global population ages and care workforce shortages intensify, the integration of Artificial Intelligence (AI) is becoming an essential driver in reshaping the elderly care industry. Taiwan's first cross-sector "AI-Powered Care Forum," organized by Anke Media, provided a comprehensive review of the current status, opportunities, and challenges surrounding AI applications in care services. More than just a tool for efficiency, AI is viewed as a transformative force that enables personalised, predictive, and collaborative care models.
Beyond Equipment: Reconstructing the Care Value Chain
The forum gathered over a hundred experts from industry, government, academia, and research, focusing on how AI is prompting a rethinking of the roles, processes, and value propositions across the entire care ecosystem. Participants emphasized that AI adoption is not merely about upgrading equipment but represents a fundamental restructuring of service delivery and operational management.
Three major trends are shaping this transformation: the technological advancement of AI itself, the evolution of intelligent service processes, and the reorganisation of the healthcare technology market. As generative AI and sensor technologies become more accessible, AI is transitioning from an auxiliary tool into an active partner in service design, risk prediction, record management, and even emotional support in caregiving scenarios.
A structured classification of AI applications in care was introduced, spanning 9 key categories:
Management Platforms
Fall and Behaviour Detection Systems
Vital Signs and Risk Monitoring
Environmental Safety Management
Smart Robotics
Personal Health Management Platforms
Rehabilitation and Mobility Aids
AI-Powered Voice Interaction
Dementia Care Solutions
These 9 categories were previously covered in detail in our feature article, AI Care Evolution – Part 2. For an in-depth exploration, please refer to the full report here: AI Care Evolution – Part 2: Product Categories Driving the Future of AI in Care
These categories underline the sector’s shift from isolated device improvements toward integrated, holistic care systems. The future potential of multimodal AI suggests that applications will not only save time, labour, and cost but also deliver care that is more timely, intuitive, and compassionate, bridging gaps in human resources while extending the capacity and reach of care services.
Policy Support: Opening New Avenues for AI in Care
Government initiatives are playing a critical role in accelerating AI adoption in healthcare. Taiwan's Ministry of Digital Affairs (MODA) has launched supportive measures ranging from infrastructure resources and funding subsidies to collaborative matchmaking platforms. These programs aim to facilitate partnerships between technology innovators and care providers.
A key focus is the development of sovereign AI, including large language models tailored to Taiwan’s healthcare landscape, enhancing the contextual relevance and applicability of AI solutions in local care settings. MODA’s “Smart Rainforest” initiative specifically prioritizes healthcare-related collaborations to bridge the gap between technology supply and real-world care needs.
These efforts align with broader international trends where public policy is essential in balancing innovation with ethical considerations, data governance, and privacy protections, especially in sectors as sensitive as elder care.
Addressing Core Challenges: Data, Ethics, and Implementation
Industry experts at the forum also highlighted critical barriers that are relevant worldwide. Successful AI deployment requires more than technical capacity—it demands organizational adaptation, cross-department collaboration, and clear ethical guidelines. Data fragmentation, lack of standardized formats, and regulatory uncertainties remain significant obstacles to scalable AI solutions in care.
A phased implementation strategy—starting with small-scale trials and building digital literacy within care teams—was recommended to foster a culture of human-AI collaboration. Additionally, roles such as “informatics nurses” are seen as crucial bridges between technology and frontline caregiving.
Industry Insights: From Concept to Real-World Impact
Care tech solution providers shared practical insights on deploying AI-driven IoT systems across various domains, including cognitive health, fall prevention, medication management, and environmental monitoring. Their experience revealed that fragmented on-site needs remain a challenge, reinforcing the necessity for platform-based solutions that enable modular integration and predictive personalization.
Senior care institutions also pointed out that while AI tools like fall detection and infection risk alerts are being piloted, widespread scalability is hindered by high deployment costs, inconsistent data standards, privacy concerns, and unclear liability frameworks. Additional government subsidies and regulatory guidance were identified as key enablers for overcoming these hurdles, particularly for small and medium-sized care facilities.
Global Relevance: Localizing AI for Diverse Care Environments
The forum concluded with reflections on the importance of aligning AI solutions with the actual needs of care environments and their users, not merely focusing on technological capabilities. Key considerations include understanding target problems, user demographics, and care timelines before developing or implementing AI solutions.
Global examples from Japan, Singapore, and South Korea demonstrate that while AI holds promise for breaking language and geographic barriers, true success depends on deep localization, adapting to each country’s regulations, cultural norms, and care practices. For international stakeholders, this signals the importance of co-creating solutions with local partners to ensure meaningful, sustainable impact.
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