The Rise of AI Agents in Data Governance Initiatives | Intelligent Enterprise Governance Systems | AGPH Books
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Book Title: The Rise of AI Agents in Data Governance Initiatives | Intelligent Enterprise Governance Systems | AGPH Books
The Rise of AI Agents in Data Governance Initiatives provides a detailed and structured study of the growing role of intelligent agents in modern enterprise data governance systems. The book explains how organizations are transitioning from traditional rule-based governance models toward intelligent, automated, and autonomous governance ecosystems driven by Artificial Intelligence technologies. It presents both theoretical concepts and practical applications related to AI-driven governance architectures, intelligent automation, metadata management, compliance monitoring, and autonomous operational control.
The book begins with the foundations and limitations of legacy data governance systems, followed by the evolution of modern governance frameworks influenced by cloud computing, big data, and real-time processing environments. It further explores AI, machine learning, and intelligent automation concepts before introducing AI agents as a new governance paradigm capable of autonomous reasoning, task execution, and adaptive decision-making.
Practical governance applications such as automated data quality management, smart classification and tagging, dynamic lineage analysis, policy enforcement, and Master Data Management optimization are examined in detail. The book also discusses governance risks, explainability, audit trails, bias management, compliance frameworks, and Human-in-the-Loop governance mechanisms. The concluding chapters provide insights into self-healing ecosystems, autonomous governance agents, and future enterprise architectures with minimal human intervention. The book serves as a valuable academic and professional resource for students, researchers, governance professionals, enterprise architects, and technology practitioners.
About The Publisher:
AGPH Books is a professional self-book publishing house based in Central India, specializing in academic, professional, fiction, and non-fiction books in print, digital, and audio formats. The publishing house produces textbooks, research and reference works, biographies, self-help titles, children's books, literary fiction, poetry, and general interest publications. With a transparent publishing process and strong digital distribution, AGPH Books ensures global availability through Google Books, Amazon, Flipkart, and its official website store, supporting authors and institutions in reaching a wide and diverse readership.
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About the Author
Madhukar Dongala is a highly experienced Data Governance and Master Data Management (MDM) professional with more than 12 years of expertise in enterprise data solutions, cloud governance platforms, and intelligent data ecosystems. His experience spans across industries including healthcare, banking, financial services, retail, and technology, where he has led large-scale initiatives focused on data quality, metadata management, governance automation, and digital transformation. Madhukar has worked with globally recognized organizations such as Take Two interactive INC, Whataburger, Novant Health, Blue Cross Blue Shield, JP Morgan Chase, and City National Bank, delivering scalable solutions using Informatica MDM, Axon, EDC, IDMC, Customer 360, and Product 360 technologies. His work focuses on building trusted, AI-ready data foundations by integrating governance, automation, and cloud-native architectures. In this book, he shares practical insights into how AI agents are redefining modern data governance and enabling organizations to move toward autonomous, intelligent, and self-sustaining data ecosystems. His research work examines the role of AI agents in modern data governance with a focus on autonomous decision making, smart metadata management, dynamic policy enforcement and continuous data quality control in distributed enterprise environments. His core competence is building AI-ready governance ecosystems that combine automation, machine learning and metadata intelligence to deliver scalable, self-sustaining and resilient data architectures. Madhukar’s research and industry work focuses on how organizations can evolve from traditional reactive governance models to intelligent, predictive and adaptive governance frameworks powered by AI-driven agents, real-time lineage intelligence and automated stewardship capabilities.
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