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{ "item_title" : "Scaling Data and AI Governance", "item_author" : [" Yvonne Wickramasinghe", "Nuran Kasthuriarachchi "], "item_description" : "Data volumes are compounding, AI adoption is outrunning oversight, and regulators are turning principles into binding obligations. Yet most organizations still run data governance and AI governance as two programs with two budgets, and the gap between them is where the next incident will come from. Scaling Data and AI Governance argues that the two disciplines are stages of a single program, and shows leaders and practitioners how to build it. The book introduces the Unified Data and AI Governance Maturity Model, which assesses organizations across eight areas, from strategy and leadership to AI lifecycle management, ethics, fairness, and transparency. It provides a six-step assessment method, business-case and ROI guidance, and an eight-step, four-phase implementation roadmap. Readers can also learn to select a governance model, define key data and AI roles, develop five essential policies, and choose suitable technologies, including data catalogs, AI governance platforms, and cloud-native controls. The book draws on established frameworks and regulations, including DAMA-DMBOK, DCAM, CMMI, NIST AI RMF, ISO/IEC 42001, the EU AI Act, GDPR, and guidance from the United Nations and UNDP. Seven case studies across banking, healthcare, government, technology, and manufacturing demonstrate practical applications at different organizational scales. Further chapters explore autonomous AI agents, data mesh, data fabric, emerging regulations, and responsible governance. Ten appendices provide practical tools, templates, checklists, and technology selection guidance to help readers turn governance principles into action. ", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/886/883/9798868835773_b.jpg", "price_data" : { "retail_price" : "64.99", "online_price" : "64.99", "our_price" : "64.99", "club_price" : "64.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Scaling Data and AI Governance|Yvonne Wickramasinghe

Scaling Data and AI Governance : A Comprehensive Guide to Building Trusted Data and Responsible AI

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Overview

Data volumes are compounding, AI adoption is outrunning oversight, and regulators are turning principles into binding obligations. Yet most organizations still run data governance and AI governance as two programs with two budgets, and the gap between them is where the next incident will come from. Scaling Data and AI Governance argues that the two disciplines are stages of a single program, and shows leaders and practitioners how to build it.


The book introduces the Unified Data and AI Governance Maturity Model, which assesses organizations across eight areas, from strategy and leadership to AI lifecycle management, ethics, fairness, and transparency. It provides a six-step assessment method, business-case and ROI guidance, and an eight-step, four-phase implementation roadmap. Readers can also learn to select a governance model, define key data and AI roles, develop five essential policies, and choose suitable technologies, including data catalogs, AI governance platforms, and cloud-native controls.


The book draws on established frameworks and regulations, including DAMA-DMBOK, DCAM, CMMI, NIST AI RMF, ISO/IEC 42001, the EU AI Act, GDPR, and guidance from the United Nations and UNDP. Seven case studies across banking, healthcare, government, technology, and manufacturing demonstrate practical applications at different organizational scales. Further chapters explore autonomous AI agents, data mesh, data fabric, emerging regulations, and responsible governance. Ten appendices provide practical tools, templates, checklists, and technology selection guidance to help readers turn governance principles into action.

This item is Non-Returnable

Details

  • ISBN-13: 9798868835773
  • ISBN-10: 9798868835773
  • Publisher: Apress
  • Publish Date: May 2027

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