Artificial Intelligence (AI) is revolutionizing Business Intelligence (BI), reshaping how organizations analyze, interpret, and leverage data for decision-making. AI-driven BI systems automate complex data processes, enabling businesses to extract, transform, and analyze information with unprecedented speed and accuracy. From real-time data streaming to predictive modeling, AI improves operational efficiency, uncovers actionable insights, and drives strategic growth. This paper delves into key advancements such as cloud-based BI, autonomous learning models, and ethical AI governance, highlighting how these innovations empower businesses to make informed, data-driven decisions. The article also deals with AI-driven BI challenges, including data privacy concerns, biases in algorithmic decision-making, and integration complexities with legacy systems. Addressing these issues requires a multidisciplinary approach, focusing on explainable AI, real-time analytics, and ethical compliance frameworks.

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AI-Powered Business Intelligence: A Review of Innovations, Applications, and Ethical Considerations

  • Youness Limame,
  • Meriyem Chergui,
  • Mohammed Ouzzif,
  • Mohamed el Kamili

摘要

Artificial Intelligence (AI) is revolutionizing Business Intelligence (BI), reshaping how organizations analyze, interpret, and leverage data for decision-making. AI-driven BI systems automate complex data processes, enabling businesses to extract, transform, and analyze information with unprecedented speed and accuracy. From real-time data streaming to predictive modeling, AI improves operational efficiency, uncovers actionable insights, and drives strategic growth. This paper delves into key advancements such as cloud-based BI, autonomous learning models, and ethical AI governance, highlighting how these innovations empower businesses to make informed, data-driven decisions. The article also deals with AI-driven BI challenges, including data privacy concerns, biases in algorithmic decision-making, and integration complexities with legacy systems. Addressing these issues requires a multidisciplinary approach, focusing on explainable AI, real-time analytics, and ethical compliance frameworks.