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The artificial lift selection process performed by human involves iterating of several design parameters. Moreover, the human's curated selection required the decision making with unbiased, repeatable and reliable. Capturing the lesson learned from the previous mistake into the new design and lack of look back in the past performances are the limits of human. The supervised machine learning method can apply to improve selection process. This approach can minimize the life-cycle cost of artificial lift wells by using machine learning which incorporate the past performances and lesson learnt from installations. The data is prepared into a structured dataset. The dataset is pre-processed to determine the "Good" and "Bad" wells based on their life-cycle cost, then used for training and validating the classification models. The most simple and accurate model is adopted for future artificial lift selection and current wells’ performance assessment. Finally, the performance of new wells is continuously added for further model's training. The artificial lift suggested by the machine learning expects reducing life-cycle cost in the ongoing trial in the fields. In term of assessing tool, the selection model reveals some discrepancy in the current installed artificial lift. This alerts the operator to look inside the potential problems. However, the subject matter experts still need to give an adequate interaction in case of false alarm. Therefore, the discovered pattern for good artificial lift selection will help improve the fields’ production. In addition, the endless learning capability of machine learning allows the new data feeds into the existing dataset and further incorporates the model in order to response to the dynamic change of the fields’ conditions. In conclusion, machine learning process is more comprehensive comparing to the selection made by conventional process where only few tables used for the artificial lift selection and overlook the value of data captured. The Artificial Intelligence is one of the emerging technologies which provides the breakthrough results. This paper presents the artificial intelligence trend in oil and gas industry. It is a promising tool which help solving human's complex problems. Ultimately, adding the durable competitive advantage to the oil and gas industry.