Symbiotic AI and equitable digital health: toward trustworthy and inclusive health ecosystems

Digital health has accelerated rapidly through advances in telemedicine, wearable technologies, artificial intelligence (AI), remote monitoring, and interoperable healthcare infrastructures. Despite these developments, substantial inequities persist among underserved populations, including rural and remote communities, older adults, low-socioeconomic groups, and geographically isolated populations exposed to infrastructure disruptions caused by avalanches, landslides, storms, flooding, or prolonged power outages. Current digital health approaches frequently emphasize technological innovation and connectivity while underestimating the importance of trust, contextual adaptation, resilience, health literacy, and human guidance. This Perspective argues that equitable digital health requires a shift from isolated AI tools in primary health services toward resilient symbiotic health ecosystems in which clinicians, patients, caregivers, communities, and AI systems collaboratively support healthcare delivery. Building on emerging research on symbiotic intelligence, health empowerment, telemedicine, rural resilience, and trustworthy AI, we propose a conceptual perspective in which calibrated human-AI collaboration becomes central to equitable healthcare delivery. The article discusses how resilient and locally adaptive infrastructures-including telemedicine, wearable monitoring, low-risk diagnostic technologies, local AI systems, backup energy systems, drones for medicine delivery, local Wi-Fi preparedness, and community-supported transport models-may strengthen healthcare preparedness and continuity in underserved and disrupted contexts. Although several examples are drawn from Norway and rural Nordic contexts, the conceptual framework is intended to be transferable to underserved populations globally. Finally, this Perspective highlights the need for implementation-oriented, equity-centered, and epistemically transparent approaches to future digital health ecosystems, exemplified through five models.