Investing in the stock market carries inherent risks, but with a disciplined approach, it can be one of the most effective ways to achieve significant returns and profits. To succeed, investors and stock traders must employ techniques to predict which stocks are likely to rise so they can buy them, and also identify the stocks anticipated to decline in value for selling purposes. Nonetheless, the volatile nature of the stock market still renders it a considerably risky investment option. In the present day, numerous researchers have dedicated their endeavors to predicting the stock market. Researchers have used various deep learning models to predict the stock market. Therefore, we have conducted this systematic review in order to examine the trends in scientific papers concerning artificial intelligence models used in stock market prediction during a period of 12 years, 2011–2023. In the end, 244 papers were identified to highlight the artificial intelligence models and families that are most frequently used for this purpose.