DEMYSTIFYING AI-DRIVEN PERFORMANCE OPTIMIZATION: A TECHNICAL DEEP DIVE

Abstract

AI-driven performance optimization has revolutionized how organizations approach system efficiency and resource management in the digital era. This comprehensive article examines the evolution from traditional manual optimization methods to sophisticated AI-driven solutions, highlighting significant improvements across various sectors. The article explores core frameworks, including advanced data collection infrastructure, intelligent analysis engines, and dynamic optimization layers, supported by real-world implementation examples from e-commerce, video streaming, and enterprise systems. The article demonstrates the transformative potential of AI optimization through a detailed examination of business impacts, return on investment, and sector-specific outcomes. The article further investigates emerging trends in edge computing, quantum computing integration, and AutoML evolution, concluding with practical implementation guidelines for organizations embarking on AI-driven optimization initiatives.