Our paper aims to empirically investigate the impact of artificial intelligence components on decision making and to examine its effect on financial performance of Moroccan industrial companies. Empirical primary data were collected from managers using a survey of ninety-three companies. Structural equation modelling is used to test these relationships. Our findings show that machine learning positively and significantly affects decision making. Moreover, they illustrate that computer vision positively and significantly impacts the decision making. Nevertheless, the hypothesis concerning the effect of natural neural networks on decision-making has not been confirmed. In addition, decision making positively and significantly affects financial performance. Besides, our findings indicate that decision making mediates the link between machine learning and financial performance. Decision making mediates also the connectedness between computer vision and financial performance. Nevertheless, hypothesis relating to mediating the relation between natural neural networks and financial performance is rejected. Our manuscript provides some new managerial contributions for managers of industrial organizations and explores the main components of AI and their impacts on decision making and on financial performance. Therefore, our findings will help managers in Morocco and in other countries to introduce artificial intelligence as a secure mechanism for enhance financial performance and mitigate risk.