When Algorithms Meet Empathy: What AI Needs to Learn From Nurses

Artificial intelligence is entering the clinical workspace faster than most nurses ever imagined. Algorithms flag abnormal results. Predictive tools suggest who is most likely to deteriorate next. Decision-support systems encourage providers to adopt specific interventions. The conversation often frames this shift in one direction: nurses must learn to understand AI. That is true. But the reverse is just as important. AI must also learn from nurses.

Machines process patterns at a scale no human could match. They can sift through lab values, imaging data, and clinical notes in seconds. What they lack is context. A patient who misses a blood pressure check might be flagged as “non-compliant.” A nurse at the bedside sees something different. The patient is a grandmother who skipped her appointment because her daughter was unable to get off work to drive her. No algorithm captures that nuance. Nurses do.

This is the hidden skillset that nurses bring to digital health. It is not just about knowing how to click the right box in an electronic record. It is about recognizing when a number does not tell the full story, when a patient’s silence hides fear, and when a cultural belief shapes decision-making. These insights are a kind of data, too. If AI tools ignore them, they risk making recommendations that look precise…