"medical records are seamlessly unified, appointments scheduled effortlessly with AI, and follow-up care is meticulously managed. Prescriptions arrive at discharge, logistics run smoothly, and physicians focus fully on patients while AI handles documentation, coding, and care coordination. After visits, patients receive structured follow-ups, medication reminders, and secure communication for ongoing support. AI continuously monitors health data, alerting clinical teams about potential risks and helping prevent readmissions. The result is a more personalized, efficient, and human-centered healthcare experience."
"Realizing this vision requires the healthcare ecosystem to address significant data challenges. The first challenge is the sheer volume of data: healthcare produces approximately 30% of global data, driven by sources such as electronic health records, advanced imaging technologies, and wearable devices. In addition to volume, a substantial amount of this data is isolated within legacy systems. Lastly, compliance oversight with rigorous regulatory requirements, such as HIPAA and GDPR, adds complexity to the path of integrating data for artificial intelligence."
"There is an emerging group of healthcare companies that are effectively navigating data challenges to transform with AI. According to the Enterprise AI Maturity Index, developed by ServiceNow and Oxford Economics, the average AI maturity score within the healthcare sector declined from 45 to 34 in 2025. Nonetheless, approximately 16% of organizations-designated as Pacesetters-are making significant progress. These Pacesetters view AI as a transformative resource; over one-quarter have already implemented agentic AI, and nearly half plan to do so in the coming year."
A future healthcare system personalizes care by unifying medical records, automating scheduling, managing follow-ups, and shifting documentation burdens from clinicians to AI. Prescriptions, discharge logistics, and structured post-visit communication streamline patient experience while continuous AI monitoring notifies clinical teams of risks and helps prevent readmissions. Realizing this future demands resolving major data challenges, including massive data volume (about 30% of global data), persistent legacy-system silos, and stringent regulatory requirements such as HIPAA and GDPR. A subset of organizations labeled Pacesetters is advancing agentic AI adoption and demonstrating effective data strategies despite broader sector maturity declines.
Read at Fortune
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