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This article explores how agentic AI is transforming enterprise analytics by shifting from reactive reporting to autonomous intelligence. Agentic AI systems can perceive, reason, plan, and act on their own, unlike traditional generative AI. It is worth reading because it provides a deep dive into the future of data analytics and how businesses are adapting to this change. Readers will learn about the technical architecture and strategic implementation of agentic AI, as well as how it is reshaping the role of analysts and decision-makers. The article is authored by Mohan Krishna Mannava, a recognized expert in AI and data engineering.
Key facts
- Agentic AI systems can perceive, reason, plan, and act on their own, unlike traditional generative AI.
- The agentic AI market is projected to reach $196.6 billion by 2034, with 62% of executives expecting over 100% ROI.
- Agentic AI combines large language models with cognitive modules and external tools to enable autonomous decision-making.
- A three-tier architecture is commonly used in enterprise agentic AI systems, with distinct roles for foundation, workflow, and autonomous tiers.
- Agentic AI is redefining analytics by moving from static dashboards to proactive intelligence that predicts needs and identifies insights automatically.
TAGS:
#Agentic AI #AI #AI Architecture #Autonomous Systems #Business Intelligence #Data Analytics #Data Engineering #Enterprise Analytics #machine learning #Strategic Implementation
