Many organizations struggle to make the most of their data, despite significant investments in cloud technology and AI tools. Traditional data management methods fall short due to complexity and pace, leading to delayed decisions and contextual deficiency. Agentic data management platforms, on the other hand, are context-aware, AI-driven systems that empower intelligent agents with real-time, unified, and governed data across an enterprise ecosystem. These platforms unify data, embed governance and quality metrics, provide specialized AI agents with historical context, create self-learning feedback loops, and automate contextual data preparation and governance. They offer capabilities beyond traditional systems to support intelligent, autonomous data operations, streamlining complexity, data integrity, and enabling real-time decision-making. Agentic platforms are urgently needed due to the convergence of AI adoption, rising data costs, and emerging multi-agent architectures, addressing challenges such as inconsistent definitions, static governance, delayed decisions, and contextual deficiency. When evaluating agentic data management solutions, consider unified schema management, embedded governance and compliance, real-time processing, and AI transparency, while also considering implementation factors like organizational readiness, context foundation, integration management, and security alignment. Acceldata's agentic data management platform combines data observability, governance, and automation into a unified solution for modern AI-driven environments, enabling data teams to operationalize data with intelligent agents that learn from historical patterns and optimize performance in real-time.