This book builds a unified data governance framework that spans the entire lifecycle of large language model retrieval, generation, inference, memory, and autonomous multi‑agent systems. The framework integrates three disciplinary lenses—technology, law, and economics—and addresses data quality, lineage and provenance, global data protection and intellectual property, the economics of data governance, digital trust and zero‑trust security architecture, ethics and responsible AI, governance of generative AI pipelines, governance of agentic AI and multi‑agent systems, data governance in elections and the public sphere, AI regulation across six jurisdictions, and the design of a governance control plane for 2030. The work consists of eleven chapters and eight appendices, anchored in Indian law while offering comparative cross‑jurisdictional insights.
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