AI-DRIVEN CLOUD DATA ANALYTICS FRAMEWORK FOR INTELLIGENT ENTERPRISE DECISION SYSTEMS
Abstract
The exponential growth of enterprise data assets, coupled with the proliferation of cloud computing platforms and artificial intelligence capabilities, has fundamentally reshaped how organisations design and operationalise decision support systems. Cloud data analytics, powered by AI and machine learning, enables enterprises to process petabyte-scale datasets in real time, deriving actionable intelligence that drives competitive advantage, operational efficiency, and strategic agility. This research paper presents a comprehensive investigation into AI-driven cloud data analytics frameworks for intelligent enterprise decision systems, systematically examining how contemporary AI methodologies—including deep learning, federated analytics, natural language processing, and reinforcement learning—are integrated with cloud-native data architectures to deliver scalable, secure, and explainable decision intelligence. Through a rigorous mixed-methods approach encompassing systematic literature synthesis, quantitative machine learning benchmarking, and four empirical case studies spanning financial services, healthcare, retail, and manufacturing, this study demonstrates that enterprises adopting mature AI-driven cloud analytics frameworks achieve decision latency reductions of 34–58%, improve forecast accuracy by 22–41%, and reduce operational costs by 19–35% within three years of implementation. The paper further examines persistent challenges including data quality governance, model explainability, multi-cloud interoperability, real-time processing constraints, and regulatory compliance complexity. A forward-looking framework integrating autonomous analytics agents, causal AI, and edge-cloud intelligence convergence is proposed. The findings underscore the critical imperative for integrated, governance-driven, and human-centric AI analytics frameworks that treat decision intelligence not as a retrospective reporting function but as a proactive, real-time strategic capability.
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