The collective intelligence that emerges when multiple AI experts with diverse training data, reasoning frameworks, and cognitive profiles analyze the same problem independently before their outputs are synthesized. Inspired by ensemble methods in machine learning — where combining multiple weak models produces a strong one — ensemble intelligence in decision-making produces recommendations that are more robust, nuanced, and calibrated than any single expert could achieve alone.
The key requirement is genuine diversity: each expert must differ in how they think, not just what they say.