A curated collection of essential ai governance & risk resources, organized by type for easy navigation.
36 resources
6 items
Navigate the complex legal landscape of AI liability. Understand product liability, professional negligence, algorithmic accountability, and emerging AI-specific liability frameworks across jurisdictions.
Most AI failures show warning signs 3–6 months before collapse. Learn the diagnostic framework to catch problems while they're fixable.
Comprehensive guide to China's AI regulatory framework - algorithm registration, security assessments, data requirements, and practical compliance strategies for organizations operating in the Chinese market.
Complete guide to mandatory bias testing requirements across NYC Local Law 144, EU AI Act, and emerging state regulations. Practical audit frameworks, documentation standards, and compliance strategies for AI systems.
Navigate IP law for AI systems. Understand copyright in training data and AI outputs, patentability of AI inventions, trade secret protection for models, and licensing frameworks for AI-generated content.
Comprehensive guide for AI compliance professionals. Understand regulatory frameworks, governance structures, risk management, audit processes, and cross-functional collaboration for enterprise AI compliance programs.
6 resources
6 items
Step-by-step checklist for achieving EU AI Act compliance by August 2027.
Complete guide to setting up an AI Governance Committee including composition, charter template, RACI matrix, and meeting cadence.
Complete guide to board-level AI risk reporting with downloadable template, best practices, and common mistakes to avoid.
Learn proven strategies to communicate your AI policy effectively. Includes stakeholder mapping, phased rollout plans, training design, and measurement frameworks.
Build foundational AI governance with a comprehensive model inventory. Policy template for registration requirements, implementation guide, and discovery methods.
Design effective AI approval workflows that balance governance rigor with operational speed. Includes templates and decision frameworks.
3 resources
3 items
Real case studies of AI project failures across industries—from Amazon's hiring algorithm to IBM Watson Health. Learn what went wrong and how to avoid similar mistakes.
Future outlook on AI regulations
78% of AI systems show measurable bias, yet only 31% of organizations test for it. Learn from real bias failures costing companies millions in lawsuits, fines, and reputation damage.
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