Highlights the growing influence of real-time data in powering self-driving AI models and autonomous decision-making. Examines the evolution of OLAP systems from traditional, batch-based frameworks to modern, high-concurrency architectures tailored to Agentic AI. Explores how these next-generation OLAP solutions handle massive query workloads, enabling instant insights and robust product analytics. Addresses key challenges—performance, scalability, and cost-efficiency—and how they are overcome by advanced OLAP platforms. Demonstrates how high-concurrency analytics fuels AI systems that learn, adapt, and act autonomously, delivering transformative, data-driven outcomes across industries.