Conversational AI in healthcare is reducing patient portal overload with urgency tagging, AI-assisted responses, and intelligent message routing. Learn what's deployed and what the evidence shows.
Overview An eye surgery center was losing patients. Not to competitors, but to no-shows. Eighteen percent of scheduled appointments went unfilled every week. Four full-time staff members spent their days calling roughly 500 patients, trying to confirm appointments. When that didn't work, the clinic overbooked randomly, hoping the math would balance out. Some days every patient showed up, and the waiting room was chaos. Other days slots sat empty.
This special report from National Technology News evaluates the key talking points from the event including everything from data readiness and governance to organisational resistance, sustainability concerns, and the future role of humans in increasingly automated workplaces. AI has moved beyond experimentation and into the mainstream. Across industries, organisations are racing to identify use cases, improve productivity, and demonstrate returns on investment. Yet while enthusiasm remains high, many businesses are discovering that turning AI ambition into measurable operational impact is far more challenging than anticipated.
Agentic AI in Healthcare A multi-agent AI system recently diagnosed rare medical cases correctly over 80% of the time. That's four times better than seasoned human clinicians. It didn't get there by being smarter than any single AI. It got there by having multiple agents argue with each other until the errors got caught.
FHIR is the REST API standard transforming healthcare data exchange. Learn how the VA and FDA use FHIR APIs for automated adverse event reporting, and what it means for your health system.
Agentic AI architecture assigns specialised AI agents to distinct tasks so the combined result outperforms any single model. Learn core components, patterns, and decision frameworks.