Building Trustworthy & Scalable AI for Healthcare

Singapore’s National AI Strategy 2.0 is shaping a transformative vision: to become a global AI hub by 2030, placing artificial intelligence at the core of healthcare and public services. Beyond experimentation, the strategy focuses on practical, trustworthy AI solutions that deliver meaningful results for patients, healthcare professionals, and citizens alike. 

AI is already transforming operations across hospitals and government agencies. By leveraging agentic AI workflows, institutions can enhance diagnostics, automate administrative tasks, streamline claims, and improve engagement with patients and citizens. Initiatives such as MERaLiON, a Singapore-developed Large Language Model, demonstrate how domain-specific AI allows professionals to focus on their core responsibilities while boosting operational efficiency and supporting better decision-making. 

The impact goes beyond individual hospitals. With robust AI infrastructure and capabilities, hospitals, social services, and government agencies can harness AI to create smarter, more responsive, and efficient services, amplifying the positive effects of AI across the public sector. 

Yet, achieving this vision comes with real challenges. At the heart of these challenges is “Data”. Clinical, administrative, and service records are often fragmented across multiple systems, which can limit real-time insights and comprehensive decision-making. Ensuring high-quality, well-governed data with a clear strategy, strong governance, and well-defined lineage is critical. 

Moreover, as Singapore advances its Electronic Health Records (EHR) transformation, reliable data becomes the foundation for AI, ensuring outputs are accurate, trustworthy, and free from bias, safeguarding patient safety, enhancing public services, and enabling sustainable transformation across healthcare and the broader public sector. 

This raises a critical question: how can healthcare and public sector institutions implement end-to-end AI systems with integrated guardrails and security to deliver scalable, reliable, and trustworthy workflows? 

A Platform-Driven Approach to Scalable AI 

To answer this, healthcare and public sector institutions need end-to-end AI platforms that bring together data, tools, and workflows to build, test, and scale AI efficiently, while maintaining trust, security, and compliance. 

• Secure, Sovereign Infrastructure: Platforms provide high-performance computing for AI workloads with built-in guardrails for sensitive data. Private cloud environments ensure that data remains within national boundaries, meeting sovereignty and privacy requirements. 

• Integrated Data Management: Platforms unify fragmented data sources into a trusted, auditable source of truth. Robust governance and lineage tracking ensure every piece of data is traceable and reliable. 

• Streamlined Development and Operations (MLOps): MLOps tools automate the AI lifecycle from data ingestion and model training to deployment and monitoring, allowing teams to move efficiently from proof-of-concept to production. 

• Operational Excellence: Integrated monitoring and orchestration maintain model accuracy and reliability over time, detecting and managing drift to ensure safe and trustworthy AI outcomes. 

With this integrated foundation, hospitals and government agencies can accelerate innovation. Clinicians can focus on patient care, administrators can streamline operations, and decision-makers can access timely insights, all supported by AI systems designed to scale safely across diverse workflows. 

Join the OpenGov Breakfast Insight to interact with senior leaders from Singapore’s public and healthcare sectors and explore how the integrated AI Factory platform can overcome unique challenges, accelerate AI adoption, and unlock transformative potential. 

Engage with peers to share insights, learn best practices, and envision how advanced, secure, and scalable AI infrastructure can empower your organisation to deliver smarter, more responsive services and care. 

In this session, you will explore how to: 

• Modernise AI Infrastructure: Deploy turnkey, secure, and scalable platforms tailored for sensitive public and healthcare data. 

• Simplify AI Deployment: Leverage integrated tools for rapid development, training, and lifecycle management of AI models. 

• Strengthen Data Privacy and Sovereignty: Ensure compliance-driven governance and maintain national control of critical information. 

• Accelerate AI Adoption: Bridge the gap between pilots and full-scale production, reducing complexity and risk. 

Who should attend: 

• Chief Information Officers 

• Chief Information Security Officer  

• Chief Medical Information/Chief Clinical Information Officer 

• Chief Operating Officers 

• Chief Data Officers 

• Chief Transformation Officers 

• Chief Technology Officers 

• Chief Digital Officers 

• Chief AI Officers 

• Chief Analytics Officers 

• Chief Innovation Officers 

• Directors and Heads of Analytics and Information Management 

• Directors and Heads of Applications 

• Directors and Heads of Cloud Architecture 

• Directors and Heads of Data 

• Directors and Heads of IT Infrastructure 

• Directors and Heads of Technology Capabilities and Innovation 

• Directors and Heads of Technology, Strategy and Policy 

• Directors and Heads of IT Security 

• Head of AppSec 

• Head of Data Science 

• Head of DevOps 

• Head of IT Operations 

Info: Automated Exposure Validation: A New Chapter in Public Sector Cyber Resilience

Also check out other Workshops in Queenstown, Meetups in Queenstown, Health & Wellness events in Queenstown.