Noah M. Kenney
§ Textbook — first edition Free · 488 pages · 2026 Index/Textbook Rev. 2026.1
The textbook — first edition, 2026

Governing Intelligence.

Law, privacy, security, and compliance in the age of artificial intelligence.

A 488-page operational textbook on AI governance, from the EU AI Act and the GDPR to NIST, ISO/IEC 42001, HIPAA, GLBA, and FERPA. Built around the AI Governance Stack, a five-layer implementation model developed across a decade of field work in regulated industries. Free to read and share.

Pages
488
Chapters
20 + 3 appendices
Edition
First, 2026
01 / Reach & Reception

An industry-defining reference — from the moment it launched.

Published in April, 2026, Governing Intelligence is already regarded as the most comprehensive AI governance framework in circulation, a reference text for the field rather than one voice within it.

It has been adopted by universities as course material, referenced by Fortune 500 companies to stand up internal governance programs, and used by government agencies as a framework for AI policy and procurement evaluation.

Messages have already arrived from members of the U.S. federal government, NATO, the United Nations, and teams at Anthropic and Meta, among others.

i. Industry-defining — widely regarded as the most comprehensive AI governance framework in circulation. Published April 2026
ii. Universities — adopted as course material in AI governance, privacy, and security curricula. Academic adoption
iii. Fortune 500 — referenced for internal AI governance program development. Enterprise use
iv. Governments — used as a framework for AI policy and procurement evaluation. Public sector
Read by — U.S. Federal Government NATO United Nations Anthropic Meta Fortune 500 teams Universities worldwide
02 / About the Book

A working manual for governing real systems.

The central thesis: AI governance is not a statement of principles, it is an operational system, built in layers, and auditable end to end.

Drawing on a decade of implementation work across healthcare, financial services, government, and mission-driven organizations, Governing Intelligence translates the global regulatory landscape, the EU AI Act, GDPR, NIST AI RMF, ISO/IEC 42001, HIPAA, GLBA, FERPA, and sectoral U.S. and international regimes, into an executable framework teams can actually build against.

Each chapter pairs legal and regulatory analysis with concrete implementation patterns, risk mappings, and governance-in-practice callouts connecting statutory language to specific layers of the Stack. Appendices include a phased governance checklist and a template AI System Impact Assessment, meant to be adopted and adapted, not admired.

The AI Governance Stack

—  Five layers
ILayer 01
Data GovernanceThe foundation — inventory, quality, bias, lineage, minimization.
Foundation
IILayer 02
Model GovernanceArchitecture review, fairness testing, robustness, documentation.
Model
IIILayer 03
System Integration GovernanceIntegration review, cascading-failure analysis, boundary testing.
Integration
IVLayer 04
Control & Monitoring GovernanceAccess, real-time monitoring, human override, drift detection.
Operate
VLayer 05
Audit & Evidence GovernanceContinuous documentation, audit trails, regulatory reporting.
Prove
03 / Table of Contents

Twenty chapters. One operating manual.

The table of contents below reflects the first edition. Chapters can be read independently or in sequence; each begins with key takeaways, key terms, a case study, and discussion questions suitable for classroom or reading-group use.

Part I Foundations — the AI Governance Stack Ch. 01–03
01The Imperative for AI GovernanceRegulatory definitions, risks, stakeholders, the business case, and the five-layer Stack as an organizing framework.p. 17
02The AI Governance Stack — Implementation SpecificationLayer-by-layer specifications, cross-layer explainability, metrics, and the governance maturity model.p. 30
03Ethical Frameworks & Professional ResponsibilityFoundational principles, the ACM Code, ethical decision-making, and comparative frameworks for AI.p. 37
Part II The Global Regulatory Landscape Ch. 04–07
04The EU AI ActLegislative history, risk-based classification, prohibited practices, high-risk requirements, GPAI, enforcement.p. 63
05United States AI RegulationFederal executive action, state fragmentation, FTC enforcement, sector rules, NIST standards, congressional proposals.p. 94
06Global AI RegulationChina, the United Kingdom, emerging markets, harmonization, standard-setting, multi-jurisdictional compliance.p. 125
07Intellectual Property & Artificial IntelligenceCopyright and AI-generated works, patents, trade secrets, open source AI, IP strategy for organizations.p. 157
Part III Privacy — law & engineering Ch. 08–11
08The GDPR & AIPrinciples, lawful bases, DPIAs, automated decision-making, Schrems II, enforcement, and privacy-protective AI.p. 189
09U.S. Privacy Laws Applied to AICCPA/CPRA, state regimes, KOSPA, preemption, COPPA, FERPA, enforcement patterns, multi-state compliance.p. 214
10Sector-Specific Privacy RegimesHIPAA, GLBA, FERPA, privacy-preserving techniques, de-identification, and governance integration.p. 238
11AI Privacy EngineeringPrivacy by Design, differential privacy, synthetic data, PIAs, homomorphic encryption, privacy-utility tradeoffs.p. 260
Part IV Security — threats, frameworks, programs Ch. 12–16
12Cybersecurity Foundations for AI SystemsThreat landscape, ML security as a discipline, data security, model integrity, supply chain, incident response.p. 281
13AI-Specific Security Threats & Attack VectorsMembership inference, model inversion, adversarial examples, poisoning, prompt injection, extraction, red-teaming.p. 298
14Security Frameworks & Standards for AINIST AI RMF, MITRE ATLAS, ISO/IEC 42001, OWASP ML/LLM Top 10, IEEE 7000, security-first lifecycle.p. 317
15AI Auditing MethodologiesFoundations, technical audits, fairness/bias, explainability, data quality, model cards, third-party audits.p. 336
16Building an AI Compliance ProgramProgram architecture, policy, risk classification, training, incident response, vendor risk, continuous verification.p. 355
Part V Applications & the future Ch. 17–20
17AI Governance in HealthcareRegulatory frameworks, clinical validation, privacy, ethics, CDSS, radiology AI, hospital operations.p. 375
18AI Governance in Financial Services & GovernmentModel risk management, fair lending, government accountability, cross-border financial AI, credit governance.p. 389
19Generative AI & Frontier Model GovernanceFoundation model risks, organizational governance, red-teaming, systemic risks, synthetic media, labeling.p. 404
20The Evolving AI Governance LandscapeRegulatory convergence, maturing standards, emerging governance models, preparing for transformative AI.p. 420
Appendices Reference & working templates pp. 438–487
AKey Regulatory Bodies & OrganizationsEU, U.S., U.K., Asia-Pacific, and international / multi-stakeholder bodies with scope and contact notes.p. 439
BAI Governance Checklist for OrganizationsA five-phase, 18-section checklist from foundation-setting through ongoing monitoring.p. 446
CTemplate — AI System Impact AssessmentA working template covering system, purpose, data, risk, ethics, stakeholders, and controls.p. 456
04 / How the Book Is Used

Used across industry, academia, and government.

Since publication, the book has been taken up by graduate programs, compliance and risk teams at scale, and government bodies shaping AI policy, each treating the AI Governance Stack as a practical scaffold for the work in front of them.

§ Audience 01

Universities & programs

A full-semester or module-sized text for graduate and upper-undergraduate courses in AI governance, privacy, law & policy, or responsible computing. Instructor materials available on request.

Course adoption
§ Audience 02

Governance programs

Fortune 500 and scale-up teams reference the AI Governance Stack and the appendix templates as a scaffold for internal policy, model inventories, risk taxonomies, and program design.

Enterprise use
§ Audience 03

Public-sector policy

Government teams use the book as a framework for AI policy and procurement evaluation, mapping statutory language to implementable control layers in RFPs, audits, and reviews.

Policy & procurement
§ Audience 04

Boards & executives

A readable reference for boards and C-suites, each chapter opens with key takeaways and closes with discussion questions suitable for strategy retreats and board deep-dives.

Board & executive
05 / The Learning Hub
Companion program — Free, online, structured

The textbook, extended into practice.

The Learning Hub is the online companion to Governing Intelligence, a structured, self-paced program that turns each chapter into a working exercise. Enrollment is free. Learners progress through modules, take knowledge checks, discuss with peers, and can generate a completion record for their institution or employer.

20ModulesOne per textbook chapter
06PathwaysCurated paths by role & sector
Self‑pacedStart any time, no cohort lock-in
$0TuitionFree to individuals & institutions
i. Module per chapter

Each of the book’s twenty chapters is mirrored by a Hub module, reading guide, core takeaways, key terms, and a working exercise grounded in the AI Governance Stack.

ii. Knowledge checks & quizzes

Short formative assessments at the end of each module reinforce the material and track progress. Results are saved to the learner’s portal for self-review and completion records.

iii. Discussion & case review

Each chapter’s discussion prompts and case studies are carried into the Hub, designed for cohorts, study groups, or individual reflection, with space for written responses.

iv. Role-based pathways

Curated sequences for counsel, compliance, security, ML/AI engineering, policy, and executive audiences, so teams can move through the material on the track most relevant to their work.

v. Completion records

Learners who finish a pathway receive a verifiable completion record, suitable for CPE/CLE portfolios, internal training ledgers, and institutional record-keeping.

vi. Instructor & team seats

Programs, universities, and enterprise governance teams can onboard cohorts, still free, with instructor dashboards and group progress views available on request.

06 / Read & Cite