For most of history, intelligence was measured by logic, language, and memory — the very skills now being replicated by machines. But as artificial intelligence grows more capable, another form of intelligence is proving harder to code and more vital to preserve: emotional intelligence (EI) — the ability to recognize, understand, and manage emotions in ourselves and others.

The term was popularized in the 1990s by psychologist Daniel Goleman, building on earlier work by Peter Salovey and John Mayer. They showed that success in relationships, leadership, and collaboration depends less on IQ and more on emotional awareness, empathy, and self-regulation. In neuroscience, these traits map to a complex interplay between the amygdala, which processes emotion, and the prefrontal cortex, which governs reasoning and impulse control. When these regions cooperate harmoniously, people make decisions that are not only smart, but also humane.

AI systems, meanwhile, are advancing rapidly in “affective computing” — technologies that detect and respond to human emotions using facial recognition, voice tone, and linguistic patterns. From virtual therapists to empathetic chatbots, researchers aim to simulate compassion through data. Yet despite these efforts, current AI lacks subjective experience — it can mirror emotional cues but cannot truly feel them.

This gap is more than technical; it’s existential. Emotions are not a flaw in reasoning but an integral part of intelligence, shaping memory, motivation, and moral judgment. As algorithms take over analysis and optimization, emotional intelligence remains the distinctly human interface between logic and meaning — the reason behind the reasoning.