Nature has been a great source of inspiration for many inventions and theories. One of the major benefits for this inspiration is perceiving the impossible as possible. The inception of the AI field was no exception with cognitively-inspired approaches with a dream of having an intelligent system that thinks as a human. However, this journey of human intelligence into machine intelligence has been rough and more challenging that resulted in the separation of AI from cognitive studies. In this article, we highlight the main challenges and opportunities for cognitive inspiration for AI development. We then break down the source of inspiration into four abstraction levels in which the researcher may place an inspiration from. These levels then contribute into three main stages for modeling the AI system. The two dimensional mapping from cognitive levels into modeling stages and the relation between them aims to assist the process of cognitively-inspired approaches.
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