Key Highlights
- 75% of Asia/Pacific care providers say agentic AI delivers greater productivity gains than GenAI
- 50% of providers will use advanced risk stratification for population health by 2028
- Asia/Pacific accounts for nearly 60% of the global aging population
- Agentic AI’s share of GenAI budgets will grow from 18% (2025) to 29% (2026)
- Multimodal AI will predict 50% of chronic and rare diseases before symptoms by 2030
- AI agents will be used by 33% of top-tier hospitals for real-time clinical decision support
- Quantum platforms will enable 100x faster diagnostics for 20% of leading institutions by 2030
- Singapore General Hospital’s AI chatbot saves ~660 clinician hours annually
Asia/Pacific healthcare provider organizations are at a critical inflection point. Generative AI (GenAI) is no longer an experimental initiative — it has become a strategic investment imperative. To navigate this shift, care providers need a clear roadmap that aligns AI priorities with emerging models of care delivery. IDC’s recently published FutureScape report for healthcare provides this roadmap and outlines how providers can move from experimentation to measurable impact.
A key highlight of this year’s FutureScape is agentic AI, which marks a new milestone in the region’s AI maturity. According to IDC’s Agentic AI Survey, 75% of Asia/Pacific care providers report that agentic AI outperforms GenAI in delivering measurable productivity gains. However, this transition requires robust regulatory frameworks and strong human-in-the-loop mechanisms to ensure ethical, transparent, and accountable deployment.
Asia/Pacific care providers must first address care productivity, enabling clinicians and operations teams to do more with constrained resources. This begins with building a resilient and trusted data foundation that can unlock the full value of agentic AI. With productivity gains as the anchor, providers can then reimagine care delivery by integrating advanced analytics, seamless workflows, and explainability to support personalized, secure, and transparent care.
This blog highlights five of the ten key predictions from the recently published IDC report: IDC FutureScape: Worldwide Healthcare Industry 2026 Predictions — Asia/Pacific (Excluding Japan) Implications
The Next Phase of Population Health Management: Toward Data-Driven, Proactive Intervention
By 2028, 50% of healthcare organizations in Asia/Pacific will leverage advanced risk stratification tools to tackle population health, specifically focusing on the chronic disease burden and aging population.
Asia/Pacific is home to nearly 60% of the world’s aging population, and the growing burden of noncommunicable diseases continues to place sustained pressure on healthcare systems. IDC expects population health management to become more data driven and proactive, as advanced risk stratification enables earlier identification of at-risk cohorts and more effective interventions.
This shift highlights the need for interoperable data platforms that unify clinical, demographic, and social determinants of health data. A strong example is Taiwan’s AI-on-DM (Diabetes Management) initiative — the country’s first large-scale healthcare AI program. Led by the Ministry of Health and the National Health Insurance Administration (NHIA), the initiative integrates long-term type 2 diabetes data with a medical large language model (LLM) to predict and manage complication risks for more than 2 million patients, years in advance. The program is expected to expand to other chronic and complex conditions, including hypertension and cancer.
Despite this progress, fragmented data environments and digital inequity remain major barriers across the region. Providers that invest in real-time analytics, standardized data exchange, and secure data sharing will be better positioned to shift from reactive care to preventive, population-scale interventions.
Agentic AI and the Future of Patient Experience: Advancing Digital Equity and Trust
By 2028, 45% of healthcare organizations in Asia/Pacific will advance agentic AI-enabled engagement by prioritizing digital equity, cultural alignment, and trust to produce personalized and empathetic communication.
Agentic AI introduces a new model of patient engagement. Unlike traditional automation, agentic systems adapt interactions in real time by drawing on clinical context, patient-reported outcomes, and social factors. In a region defined by linguistic, cultural, and socioeconomic diversity, this capability is critical.
IDC research shows that Asia/Pacific providers are rapidly increasing investment in agentic AI for patient engagement and care coordination. IDC’s 2025 FERS Survey indicates that agentic AI’s share of GenAI budgets will rise from 18% in 2025 to 29% in 2026. A practical example can be seen in Synapxe’s efforts to modernize Singapore’s national health digital infrastructure. By embedding AI-driven decision support and intelligent automation across patient-facing and care coordination platforms, Synapxe is enabling more proactive, personalized, and culturally aligned engagement.
Trust remains foundational. Transparent AI behavior, explainable recommendations, and clear escalation paths to clinicians are essential for adoption by both patients and care teams. Providers that embed governance, cultural sensitivity, and digital equity into agentic engagement strategies will build stronger patient relationships and improve outcomes.
Multimodal AI and the Shift to Predictive, Preventive Care
By 2030, multimodal AI will predict 50% of chronic and rare diseases before symptoms, making predictive care a reality with broader health data, including wearables and multiomics in Asia/Pacific.
This marks a decisive shift from reactive to predictive and preventive healthcare. Advances in multimodal AI — spanning clinical records, medical imaging, genomics, proteomics, and real-time wearable data — are enabling earlier and more accurate disease risk identification, often years before symptoms appear.
For a region facing rapid population aging and rising chronic disease prevalence, the impact is significant. Multimodal AI models can continuously analyze longitudinal health data to detect subtle patterns invisible to traditional diagnostics. In China, multimodal AI systems combining medical imaging, clinical records, and laboratory data have demonstrated approximately 98% accuracy in detecting biliary atresia.
Earlier detection supports targeted prevention, personalized care pathways, and reduced downstream costs. For rare but life-threatening pediatric conditions, such as biliary atresia, earlier diagnosis can dramatically improve outcomes.
Real-Time Decision Support: Governed AI Agents in Clinical Care
By 2030, 33% of top-tier hospitals in Asia/Pacific will deploy AI agents to deliver real-time decision support and autonomous workflows with greater than 80% accuracy while escalating exceptions to clinical staff.
Clinical environments demand speed, accuracy, and accountability. IDC expects AI agents to increasingly augment clinicians by synthesizing multimodal data and delivering context-aware insights at the point of care. These agents will not replace clinicians, but they will automate routine tasks and support faster, more consistent decision-making.
A real-world example is Singapore General Hospital’s AI chatbot, Peach (Perioperative AI Chatbot), which supports pre-operative assessments and saves approximately 660 doctor hours per year.
Success depends on data quality, interoperability, and governance. AI agents must operate within clearly defined boundaries, with continuous monitoring and escalation mechanisms. Hospitals that invest early in AI-ready infrastructure will improve clinician efficiency while preserving clinical oversight.
From Classical Limits to Quantum Leap: Preparing for Precision-Driven Care
By 2030, 20% of top-tier healthcare institutions in Asia/Pacific will harness quantum platforms for 100x faster diagnostics, simulations, and digital twins in precision-driven complex care.
Quantum computing remains emerging, but it represents a long-term inflection point for healthcare. IDC expects early adoption in complex diagnostics, precision medicine, and advanced simulations. Governments and institutions across Asia/Pacific are already investing in quantum ecosystems.
In Australia, the University of Wollongong’s quantum-enhanced imaging research demonstrates how hybrid quantum-classical techniques can accelerate genomics, biomarker discovery, and precision radiotherapy. For healthcare leaders, this reinforces the importance of future-ready data architectures and skills development.
Moving Forward: From Insight to Action
Together, these predictions highlight a clear message for Asia/Pacific healthcare providers. Agentic AI, advanced analytics, and emerging technologies can deliver measurable gains in productivity, patient experience, and clinical outcomes. However, success depends on trusted data foundations, interoperability, explainability, and strong human oversight.
IDC FutureScape provides a practical roadmap for navigating this transition. Providers that act now to align data, governance, and workforce strategies will be best positioned to lead in the next era of AI-driven, patient-centric care.
