5 ways Singapore is building trust in AI for better patient care

Singapore is showing how AI can transform healthcare responsibly. Rather than rushing tools into hospitals, the city-state’s hospitals, startups, research institutes and government agencies collaborate from the outset – first test innovations in controlled “sandboxes,” carefully building inclusive datasets and developing systems alongside clinicians and regulators.

This coordinated approach ensures AI isn’t just a technological experiment; it’s a tool designed to improve patient care while minimizing risk. At Ng Teng Fong General Hospital, algorithms predict bed demand before flu outbreaks, helping staff allocate resources efficiently and reduce patient wait times. At research labs like A*STAR, AI tools analyze genetic data to help clinicians spot disease risks early. Across Singapore, this combination of foresight, collaboration and real-world testing is making AI both innovative and trustworthy.

Singapore’s approach is distinctive because it treats AI as more than just a set of tools. Every step – from development to deployment – brings ethics, fairness and patient safety into consideration. Innovations are tested in real-world settings, refined with clinician input and monitored by regulators, ensuring that AI serves people rather than just hospital efficiency or profit. By combining careful oversight with cross-sector collaboration, Singapore is building a model of healthcare AI that other countries are beginning to watch closely.

Here are five concrete ways Singapore has translated its leadership in AI into practical, responsible healthcare solutions, with each approach highlighting innovation, collaboration and real-world impact:

Singapore has created regulatory sandboxes – controlled spaces where AI tools can be trialled before they reach real patients. Holmusk, a local health-tech startup, tested an AI tool in one of these sandboxes to analyze mental health patient data and flag early signs of depression. Clinicians could review the AI’s recommendations in a low-risk environment, while regulators assessed privacy and safety concerns. Even in this controlled setting, challenges emerged: Results could differ when the tool is deployed at scale, and testing required careful coordination and resources. Yet these sandboxes provide a rare chance to experiment safely, giving developers and regulators confidence that AI tools can work as intended.

Beyond Holmusk, regulatory sandboxes in Singapore serve as a proving ground for a wide variety of healthcare innovations. Startups and research institutions can iterate on their algorithms with real-world data, while minimizing risks to patients. These sandboxes also encourage cross-sector collaboration, as developers, clinicians and regulators work side by side to refine AI systems. Such interactions not only improve the reliability of the tools but also help regulators understand emerging technologies, shaping policies that can accommodate innovation without compromising patient safety.

Sandboxes also provide important lessons for scaling AI across the healthcare system. Insights gained in controlled trials help identify potential biases in datasets, technical limitations of AI models and operational hurdles in clinical workflows. By providing this structured testing environment, Singapore’s regulatory sandboxes are laying the groundwork for AI that is not only innovative but also trustworthy, ensuring that patients benefit safely from technological advances.

Singapore's healthcare institutions are actively integrating AI into clinical settings to address real-world challenges. At Ng Teng Fong General Hospital (NTFGH), Project ENTenna is a pioneering initiative supported by the Ministry of Health’s Health Innovation (MHI) Fund and the JurongHealth Fund. This project established Asia's first population allergy database focused on allergic rhinitis (AR), a condition affecting 39% of Singaporeans.

Project ENTenna integrates patient-reported data with AI analytics to personalize treatment plans, improve medication adherence and reduce unnecessary hospital visits. AI-generated insights support clinicians in real time, including prompts for patient discharge and “right-siting” to primary care. At NTFGH, early evaluations using hospital electronic health records indicate a 45% increase in appropriate discharges from specialist outpatient care to primary care, improving clinical workflow efficiency and resource allocation.

The programme integrates AI-driven symptom trackers, chatbots and behavioral nudges, with patient-reported and EHR-based metrics demonstrating up to a 25% increase in medication adherence and engagement. A foundational AI model is being developed to enable more interactive and scalable communication, further supporting clinical decision-making in future phases.

By combining AI analytics, patient engagement tools and clinician oversight, Project ENTenna demonstrates how hospitals can safely implement AI to improve care outcomes. It highlights Singapore’s approach to embedding innovation responsibly within everyday clinical practice, ensuring technology serves both patients and providers effectively.

Singapore's National Precision Medicine (NPM) initiative is a cornerstone in addressing AI fairness. This decade-long, whole-of-government effort aims to generate precision medicine data for up to 1 million individuals, integrating genomic, lifestyle, health, social and environmental data. By collecting diverse and representative datasets, the NPM initiative seeks to mitigate biases in AI algorithms that can arise from homogeneous data sources.

The NPM initiative also emphasizes the importance of continuous monitoring and updating of datasets to reflect the evolving demographics and health trends of the population. This dynamic approach ensures that AI tools remain relevant and effective across different population groups, thereby promoting equity in healthcare outcomes. Furthermore, the initiative fosters collaboration between public institutions, private sector partners and international organizations to align standards and share best practices in AI fairness.

Singapore's approach to AI in healthcare is characterized by robust collaboration among hospitals, startups, research institutes and government agencies. A notable example is the partnership between A*STAR's Genome Institute of Singapore (GIS) and SingHealth, which focuses on developing AI-driven solutions for early cancer detection and personalized treatment. This collaboration leverages advanced AI models to analyze complex biological data, facilitating the identification of novel drug targets and biomarkers.

Such cross-sector partnerships are instrumental in translating scientific research into practical healthcare applications. They enable the pooling of resources and expertise, accelerating the development and deployment of AI technologies. Moreover, these collaborations ensure that AI solutions are designed with clinical relevance and patient safety in mind, aligning technological advancements with healthcare needs.

Singapore actively contributes to regional efforts in establishing AI governance and ethics standards. Through the ASEAN AI Health Working Group, Singapore has played a pivotal role in developing guidelines for the ethical use of AI in diagnostics and hospital management. These guidelines emphasize principles such as transparency, fairness and accountability, aiming to build trust in AI technologies across South-East Asia.

Additionally, Singapore's involvement in regional collaborations extends to capacity-building initiatives, where it shares its experiences and best practices with neighbouring countries. This knowledge exchange fosters a collective approach to addressing challenges in AI adoption, ensuring that the benefits of AI in healthcare are realized equitably across the region. By setting and promoting these standards, Singapore not only enhances its own healthcare system, but also contributes to the advancement of responsible AI practices in the ASEAN region through offering a scalable model and best practices to emulate.

By embedding trust, fairness and collaboration into every stage – from sandboxes to hospital pilots, inclusive datasets, cross-sector partnerships, and regional knowledge-sharing – Singapore demonstrates how AI can transform healthcare responsibly. Challenges remain, from maintaining privacy and fairness to coordinating stakeholders and scaling lessons regionally, but careful monitoring, regulatory updates and clinician engagement help mitigate risks.

Singapore’s experience offers a clear roadmap for other countries: considered, transparent and collaborative approaches can make AI a powerful tool for improving care without creating new risks. By keeping patients at the centre of every decision, Singapore is proving that innovation and responsibility can advance hand-in-hand, shaping a future where AI genuinely enhances healthcare for everyone.