Human intuition is an unconscious mental process aimed to solve problems without using a rational decision-making process. Meanwhile, the artificial intuition is a limited representation of human intuition, and it models intuitive ability of solving problems in order to be implemented in machines. In this work, we performed an analysis about analogies between human and artificial intuition using INPUTS, PROCESSING, and OUTPUTS. Mainly, we have focused on synthetize algorithms that improve robot performance in pick and place tasks, simplifying the processing stage (decision-making process), by reducing the complexity the set of instructions needed to solve the task. The experiments show that we reduced the execution time of the task aided by the algorithm and also augmented its accuracy. This new approach of artificial intuition can be exploited to solve current unsolved problems of artificial intelligence.