Artificial Intelligence for Data-Driven Innovation: A Systematic Review of Predictive Analytics, Deep Learning, Process Optimization, Ethics, and Real-Time Decision-Making

Abstract

Artificial Intelligence (AI) has revolutionized the concept of innovation based on data, providing predictive analytics, deep learning, process optimization, and real-time decision-making. This review delves into the methodologies of artificial intelligence, its applications in health, manufacturing, business, agriculture, and public sector, as well as its impact on operational efficiency and analytical capabilities. It also considers issues of data quality, model interpretation, complexity, privacy, security, and ethical governance. Additionally, the review highlights new potential areas for explainable AI, federated learning, and AI-driven decision support systems. The results underscore the need for a trade-off between predictive power, computation, transparency and responsible implementation for achieving sustainable and trustworthy data-driven innovation.