The paper deals with the topic of artificial intelligence in the finance and business sector. There are three categories of artificial intelligence algorithms. Supervised learning algorithms work by taking clearly labeled data during training and using it to learn and grow. Unsupervised learning algorithms use this unlabeled data to build models and estimate relationships between different data points to provide better insight into the data. In reinforcement learning, an algorithm learns by interacting with its environment, receiving feedback in the form of rewards or punishments, and adjusting its actions to maximize cumulative rewards. Artificial intelligence (AI) in finance helps generate insights for data analytics, performance measurement, forecasting and forecasting, real-time calculations, customer service, intelligent data mining and more. The behavior of AI machines is based on the data they are trained on. By simplifying and consolidating tasks and analyzing data and information far faster than humans, artificial intelligence has had a profound impact. Big data represents colossal amounts of structured and unstructured data that organizations and companies collect every day. Smart data represents smaller data sets that provide meaningful, valuable and useful information.