Artificial Intelligence and Machine Learning in Business Intelligence, Finance, and E-commerce: a Review

This research examines the transformative effects of artificial intelligence (AI) and machine learning (ML) on business intelligence (BI), finance, and e-commerce, focusing on recent advancements and emerging trends. AI and ML have significantly enhanced BI by enabling more accurate predictive analytics, real-time data processing, and improved decision-making capabilities. In the financial sector, AI-driven algorithms are revolutionizing risk management, fraud detection, and personalized financial services, leading to more secure and efficient systems. The e-commerce industry is experiencing a major shift with AI and ML enhancing customer experience through personalized recommendations, dynamic pricing, and intelligent chatbots. The paper also highlights the integration of AI with big data analytics and the Internet of Things (IoT), creating a more interconnected and data-driven business landscape. Ethical considerations and challenges such as data privacy, algorithmic bias, and the need for regulatory frameworks are discussed. Additionally, the review identifies key areas for future research, including the development of explainable AI (XAI) to improve transparency and trust, and the potential for AI to drive sustainable business practices. This paper provides a detailed overview of how AI and ML are transforming BI, finance, and e-commerce, offering valuable insights for researchers, practitioners, and policymakers looking to leverage these technologies for competitive advantage and sustainable growth.