Collective intelligence in clinical medicine: what works, what fails, and how collaboration with AI really helps

As clinical information multiplies and patient cases become more intricate, even the most experienced doctors face the limits of solitary expertise. Collective intelligence-the idea that groups of people, and increasingly people together with AI, can make better decisions than individuals-offers a promising way to meet this challenge. We define collective intelligence in medicine and explain why healthcare is a uniquely important domain for its study, given the combination of high complexity and high stakes. We then distinguish different dimensions of collective medical decision-making, and review evidence for the benefits and limits of simple aggregation of judgments ("the wisdom of crowds") and interactive decision-making through deliberation. Finally, we highlight open questions and emerging directions, with particular focus on the expanding role of human-AI collaboration. We argue that the future of collective intelligence in medicine lies not only in classic hybrid intelligence where individual human judgement can be augmented by algorithmic decisions but in truly collaborative intelligence, where deliberation across multiple hybrid teams remain central to managing uncertainty.