Artificial intelligence (AI) applications in investments have gained a lot of attention from researchers since the late 1990s when personal computers were more widely used and technology advanced more quickly. Since then, numerous strategies have been implemented to deal with the problem of forecasting stock market movements. The three domains into which the research papers were categorized were investment sentiment analysis, stock market estimation using AI, and portfolio optimization. Furthermore, the synthesis of the review indicates that the topic has attracted the interest of academicians and thus the research area is getting more comprehensive and in-depth. The machine learning models are increasingly utilized in algorithmic trading and portfolio management. The growing application of machine learning for the financial markets pushes current modeling and model implementation procedures to the test. It raises the need for workable solutions to handle the complexity associated with these methods.