AI-Ready Data (en Inglés) - Andrew Madson

Build scalable AI systems by fixing data silos, quality decay, and governance gaps

AI-Ready Data provides a structured roadmap for organizations deploying traditional AI, large language models, and agentic AI systems. Written by Andrew Madson, who has held data strategy leadership roles at Fortune 100 companies including JPMorganChase and MassMutual, the book focuses on the foundational data challenges that undermine AI outcomes. It connects AI engineering, data strategy, and infrastructure planning into a unified approach for building production-grade AI systems.

The book details how to identify and resolve data silos, quality decay, and governance gaps that create hidden costs and erode AI ROI. It covers modern data product architectures and compliance-ready systems designed to accelerate model deployment and reduce technical debt. Each chapter addresses specific operational pain points, from dirty data remediation to building scalable infrastructure that supports traditional ML pipelines, LLM integration, and agentic AI workflows.

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AI-Ready Data serves business and technology leaders, including CIOs, CDOs, CTOs, and CISOs, as well as data professionals responsible for building and maintaining the data infrastructure behind AI initiatives. It delivers actionable frameworks for resolving data quality, governance, and architecture challenges that directly affect AI system performance.