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Artificial Intelligence Regulation & Compliance

Publisher HHeuristics
Published Oct 21, 2025
Length 23 Pages
SKU # HHE20489496

Description

Explores the tri-polar global AI governance model (EU, U.S., China). Summarizes EU AI Act risk levels, U.S. deregulation, and China’s security mandates. Outlines compliance deadlines (Aug 2024–27) and enterprise readiness strategies.
Research draws on primary legal texts from the EU AI Act (2024 final version), U.S. state-level algorithmic accountability bills, China’s Interim Measures for Generative AI Services, and ISO/IEC 42001 to map the evolving global AI compliance landscape. The analysis incorporates inputs from OECD AI Policy Observatory, Stanford AI Index (2025), and BSA compliance frameworks, ensuring comprehensive coverage of both statutory and voluntary governance regimes. The study applies comparative policy analysis and regulatory impact modeling to evaluate enforcement timelines, compliance costs, and operational obligations for high-risk and GPAI systems. Findings show an accelerating move toward auditable AI systems, where transparency, documentation, and lifecycle monitoring are prerequisites for market access across multiple jurisdictions. Particular emphasis is placed on cross-jurisdictional compliance readiness—highlighting the growing importance of certification (ISO/IEC 42001), AI risk management (NIST AI RMF 1.0), and independent third-party audits as instruments of trust and competitive differentiation. The analysis concludes that aligning governance frameworks with these standards will not only mitigate regulatory risk but also unlock access to global markets by demonstrating verifiable compliance maturity and ethical AI stewardship.

Table of Contents

23 Pages
1. Executive Summary
1.1. Global Regulatory Climate and Key Developments (2024–2025)
1.2. Strategic Implications of AI Governance for Enterprises
1.3. Divergent Approaches: EU, U.S., China, and Emerging Markets
1.4. Key Challenges and Industry Readiness
2. Global AI Governance Landscape
2.1. The Tri-Polar Model: EU Statutory Oversight, U.S. Deregulatory Innovation, and China’s Centralized Control
2.2. EU AI Act: Scope, Risk Classification, and Enforcement
2.3. United States: Federal Policy Gaps and State-Level Tort Liability
2.4. China: Algorithmic Accountability, National Security, and Data Localization
2.5. Comparative Overview: Global Harmonization vs. Regulatory Fragmentation
3. The EU AI Act Explained
3.1. Framework Overview: Unacceptable, High, Limited, and Minimal Risk Tiers
3.2. General-Purpose AI (GPAI) and High-Risk System Obligations
3.3. Documentation, Testing, and Post-Market Monitoring Requirements
3.4. Penalties and Cross-Border Enforcement (2024–2027 Timeline)
3.5. Integration with Sectoral Regulations (Medical Devices, Finance, Transportation)
4. U.S. and International Regulatory Evolution
4.1. The Shift Toward Voluntary Standards (NIST AI RMF 1.0)
4.2. ISO/IEC 42001:2024 Certification and Global Audit Readiness
4.3. National and Sectoral Initiatives (UK, Japan, South Korea, and India)
4.4. Legal Liability and AI Accountability in Common-Law Systems
4.5. The Role of Multilateral Institutions (OECD, UNESCO, G7)
5. Compliance Frameworks and Implementation Strategies
5.1. Building AI Compliance Programs: Governance, Risk, and Controls
5.2. AI Audits and Conformity Assessments (Pre- and Post-Market)
5.3. Operationalizing Trust: Data Governance, Explainability, and Fairness
5.4. Certification Pathways: ISO/IEC 42001, SOC 2 AI, and Independent Audits
5.5. Aligning Compliance with ESG and Responsible AI Objectives
6. Strategic Outlook and Industry Implications
6.1. Regulation as a Competitive Advantage: Trust-Based Differentiation
6.2. Compliance Costs and Resource Allocation Benchmarks
6.3. Cross-Border Data and Model Governance Challenges
6.4. The Future of AI Assurance: Continuous, Auditable Governance
6.5. Strategic Recommendations for Compliance Leaders and Policymakers

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