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The integration of artificial intelligence (AI) in financial markets and business operations has emerged as a transformative force, reshaping traditional practices and unlocking new opportunities. This paper presents a systematic literature review encompassing a wide array of studies on AI applications in finance and business. The review explores AI's role in enhancing financial forecasting, trading strategies, risk management, and fraud detection. It discusses various AI techniques such as machine learning, deep learning, and natural language processing, highlighting their effectiveness in analysing vast datasets and improving decision-making processes. Moreover, the review addresses the implications of AI adoption in optimising business operations, including process automation, predictive analytics, and customer experience enhancement. Key themes include the benefits of AI-driven innovations, such as increased efficiency, cost reduction, and personalised services, alongside challenges related to job displacement, algorithmic bias, and regulatory frameworks. The paper concludes with insights into future research directions aimed at advancing AI's interpretability, transparency, and ethical deployment in financial and business contexts.
Prangya Khurana - (2024) studied this question.