Artificial intelligence has rapidly grown over the past few years; the development of technology and machine learning has continued to take the lead in the finance sector. However, there are still loopholes in current artificial technology, and to overcome these loopholes, data scientists and engineers have to take steps to innovate and improve artificial technology. In this research study, we explored the uses and extensive application of artificial intelligence and machine learning in the finance sector, which will provide an overview of the understanding of these technologies. This paper includes the present stage of the technologies mentioned above in the finance sector, which will be gathered from relevant literature. Specifically, the paper focuses on how these financial organizations utilize these technologies, represented by the quantitative survey findings showing application growth among various industries. It has also highlighted the growing patterns and problems that prevent the broad use of the technologies, including embedded bias, employee de-skilling, model complexity, and systemic dangers. Moreover, the paper aimed at the rapid changes in the finance sector to monitor changing patterns and to understand recent growth and developments with significant use in stock market prediction with market understanding algorithmic trading, fraud detection, etc.