AI and It Governance
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Overview
AI systems are moving from experimentation into enterprise-critical operations. The question is no longer whether to govern them, but how -- without strangling innovation.
AI and IT Governance offers a rigorous, immediately applicable answer: a unified framework bridging classical IT governance (COBIT, ITIL, ISO/IEC 38500) with machine-learning lifecycle management, EU AI Act compliance, and responsible AI deployment. Across 19 chapters in five parts, it spans foundations, key components, implementation, real-world case studies, and the future of AI governance.
At its core is the IKI-Gov reference model -- six governance domains × six lifecycle phases × six measurement points -- with a free open-source CLI assessment tool (presidio-hardened-ikigov-assess). Around it the book delivers a complete operating model: EU AI Act risk tiers and ISO/IEC 42001 conformity, adversarial-threat and model-drift risk management, GDPR-compatible data governance, ready-to-use RACI templates and three-lines-of-defence integration, quality gates G0-G5, an MLOps selection matrix, and a competency-and-culture model. Three ethics case studies -- healthcare, mortgage lending, content moderation -- show where governance gaps form and how to close them.
Regulation-aware as of Q1 2026, with 43 figures, workshop-ready checklists, and quality-gate templates for direct use.
Targetgroup
For CIOs, CAIOs, and AI product owners; compliance, legal, and data-protection teams; data scientists and MLOps engineers; risk managers and internal auditors; and graduate students in information management, business informatics, or law.
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Details
- ISBN-13: 9783662740019
- ISBN-10: 366274001X
- Publisher: Springer
- Publish Date: December 2026
- Page Count: 196
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