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This paper argues that developing quantum and quantum-like models of cognition, decision-making, and AI provides a promising pathway for narrowing, and perhaps essentially bridging, this gap. Empirical studies of human cognition and decision-making reveal systematic deviations from classical probability, logic, and information theory\u2014manifesting as contextuality, order effects, interference (such as conjunction and disjunction effects), task incompatibility, and apparent randomness. These phenomena are well captured by quantum probability theory and related quantum-like frameworks, which provide a rigorous mathematical formalism\u2014Hilbert spaces, superposition, entanglement, and decoherence\u2014for modeling cognitive states and their evolution. Such models go beyond metaphor, showing that aspects of human reasoning can be more faithfully represented using quantum-like rather than classical probabilistic structures. Although genuine quantum (based on quantum physics) and quantum-like approaches share the same mathematical foundation, they differ experimentally. Both stimulate the development of novel AI architectures: quantum AI (QAI) and quantum-like AI (QLAI). While QAI depends on advances in quantum computing, QLAI can be realized on classical digital or analog hardware. The advancement of both offers a promising route to reducing\u2014and potentially bridging\u2014the divide between natural and artificial intelligence. This paper sets out a conceptual program to unify natural and artificial intelligence via quantum\/quantum-like models of consciousness\/cognition and AI.<\/jats:p>","DOI":"10.1007\/s44163-026-00909-w","type":"journal-article","created":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T03:03:51Z","timestamp":1770519831000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Quantum-like cognition and AI toward the convergence of natural and artificial intelligence"],"prefix":"10.1007","volume":"6","author":[{"given":"Andrei","family":"Khrennikov","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,8]]},"reference":[{"key":"909_CR1","first-page":"1","volume":"240","author":"G Acampora","year":"2025","unstructured":"Acampora G. Quantum artificial intelligence: a survey. 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