A New Era for Digital Health 2026

Introduction Global health is under increasing strain. Intelligent health systems offer a pathway to unlock prevention and personalization at scale. Around the world, health systems are facing mounting pressure. Rising chronic disease, ageing populations and growing health inequities are converging with new global threats, from climate shocks to antimicrobial resistance. Non- communicable diseases now account for 74% of global deaths,¹ while mental health disorders remain among the top 10 causes of health loss worldwide.² At the same time, health workforces are shrinking, and progress on key indicators such as maternal and child mortality has stalled.³ The economic toll is immense; for example, diabetes costs more than $1 trillion each year, and cancer-related losses are projected to exceed $25 trillion in total between 2020 and 2050, while other conditions such as cardiovascular disease and obesity are also generating costs at a similar scale.4,5 Fiscal pressures are mounting, with health spending already surpassing $9.8 trillion annually – over 10% of global GDP – and continuing to rise faster than government revenues.6 Yet as much as one-fifth of this spending in OECD countries remains ineffective or wasteful.7 The cost of this imbalance is measured not only in lives, but in lost productivity, opportunity and resilience. These challenges are well known, but their convergence has created a new kind of systemic strain. Despite unprecedented advances in science and technology, the gap between what is possible and what is practised continues to widen. Without a new model, health systems will remain locked in cycles of crisis response instead of transformation. The ‘intelligence’ opportunity Over the past decade, health systems have made major progress in digitization. Hospitals and payers are digitizing records, expanding telehealth and deploying AI tools. These efforts are essential, yet digitization alone is not transformation. True progress depends on turning data into intelligence.Intelligent health systems represent a system- level leap, integrating multimodal data across clinical, genomic, behavioural and environmental domains into a unified infrastructure that transforms fragmented information into actionable insights. They enable continuous, real-time decision-making across the ecosystem, helping: –Governments shape adaptive policy –Providers improve access, quality and outcomes –Payers target resources efficiently –Individuals receive personalized, preventive care Where early digital initiatives built tools, intelligent systems build transformation. Through AI and multimodal data integration, it is possible to detect risks earlier, predict outbreaks faster and design more precise interventions. An intelligent health system amplifies the value of existing digital investments while laying the foundation for the next era of prevention, resilience and innovation, ultimately enabling: –Healthier societies: Earlier and more widespread prevention, and detailed population health intelligence (PHI) –Stronger economies: Healthier populations with greater productivity potential –Scalable innovation: Providing a platform to scale digital health from pilot to population –Personalized care: Shifting from the traditional “one size fits all” approach An intelligent health system reframes innovation as infrastructure, acting as the backbone of a system that is capable of moving from fragmented, reactive care to insight-driven, preventive and personalized health at scale. Without a new model, health systems will remain locked in cycles of crisis response instead of transformation. A New Era for Digital Health: Abu Dhabi’s Leap to Health Intelligence 7