The text explores the evolution of artificial intelligence (AI) from predictive and generative AI to the more advanced agentic AI, which operates autonomously in real-world scenarios. Unlike its predecessors, agentic AI systems possess "agency," allowing them to make decisions and execute tasks independently by understanding context and data rather than merely following direct instructions. These systems are designed to collaborate with humans, handling complex tasks with minimal oversight, and adapting to new information through continuous learning. Agentic AI's applications range across industries, from customer service to supply chain management and finance, offering increased efficiency, personalized experiences, and enhanced data-driven decision-making. Despite their potential, these systems present challenges such as ensuring security, maintaining transparency, and balancing autonomy with human oversight. The rise of agentic AI necessitates robust data infrastructure, like Aerospike’s real-time data platform, to support these systems' needs for fast, large-scale data processing. As agentic AI becomes more prevalent, it is expected to redefine workplace roles and processes, although careful attention must be given to ethical considerations and governance to ensure trust and accountability.