Artificial intelligence (AI) has rapidly evolved over the past two decades and is now widely applied across various sectors, including finance. This study provides a comprehensive review of the existing literature on AI in finance, identifying key research directions and areas requiring further investigation. Using bibliometric and content analysis, the study examines a large number of articles published between 1992 and March 2021. The literature on AI in finance has significantly expanded since the beginning of the 21st century, covering a wide range of countries and various AI applications, including predictive/forecasting systems, classification/detection/early warning systems, and big data analytics/data mining/text mining. The selected articles are grouped into ten main research streams, including AI applications in the stock market, trading models, volatility forecasting, portfolio management, performance, risk and default evaluation, cryptocurrencies, derivatives, credit risk in banks, investor sentiment analysis, and foreign exchange management. Future research should address partially unanswered questions and improve understanding of the impact of recent technological developments on finance. The study highlights the growing importance of AI in finance, its potential to enhance efficiency and productivity, and its implications for financial conduct and regulation. It also identifies key challenges and opportunities for further research in AI applications in finance.Artificial intelligence (AI) has rapidly evolved over the past two decades and is now widely applied across various sectors, including finance. This study provides a comprehensive review of the existing literature on AI in finance, identifying key research directions and areas requiring further investigation. Using bibliometric and content analysis, the study examines a large number of articles published between 1992 and March 2021. The literature on AI in finance has significantly expanded since the beginning of the 21st century, covering a wide range of countries and various AI applications, including predictive/forecasting systems, classification/detection/early warning systems, and big data analytics/data mining/text mining. The selected articles are grouped into ten main research streams, including AI applications in the stock market, trading models, volatility forecasting, portfolio management, performance, risk and default evaluation, cryptocurrencies, derivatives, credit risk in banks, investor sentiment analysis, and foreign exchange management. Future research should address partially unanswered questions and improve understanding of the impact of recent technological developments on finance. The study highlights the growing importance of AI in finance, its potential to enhance efficiency and productivity, and its implications for financial conduct and regulation. It also identifies key challenges and opportunities for further research in AI applications in finance.