<p>Artificial intelligence (AI) systems have predominantly mirrored neurotypical brain architectures (NBA), optimizing for efficiency, predictability, and standardized cognitive patterns. However, non-neurotypical brains (NNB) exhibit unique neurochemical, hormonal, and functional mechanisms that underpin divergent thinking, creativity, and alternative problem-solving strategies. Drawing from evolutionary biology, we emphasize how neurodiversity serves as a critical mechanism for adaptability, survival, and learning in complex living systems. This paper explores the cognitive benefits and pitfalls of non-neurotypical cognition as a foundation for bioinspired AI architectures. By analyzing behavioral variability, neurochemical underpinnings, and the diverse strategies enabling adaptation, we propose a proto-model for AI systems that mimic neurodivergent traits such as hyperfocus, sensory sensitivity, and non-linear associations. Such systems hold the potential to extend generative AI capabilities, fostering inclusivity, creativity, and novel problem-solving approaches across various domains. This interdisciplinary exploration challenges current paradigms in AI development and lays a pathway toward transformative technologies inspired by neurodivergent cognition.</p>