AI Governance in a Fragmented Regulatory Landscape
Mapping jurisdictions by regulatory philosophy and governance maturity
Guidance & Principles
Voluntary guidance, principles-based approaches and non-binding frameworks
Governance & Assurance Frameworks
Established governance frameworks, testing, standards, assurance mechanisms and implementation guidance
Binding Legal Requirements
Enforceable laws and regulations with binding obligations and penalties
RISK-MANAGEMENT POSTURE
Anticipatory / Preventive
Focus on preventing harm and addressing risks early
Balanced / Adaptive
Seeks proportionate risk management as capabilities evolve
Reactive / Emerging / Fragmented
Responds to risks or is at an early stage of regulation
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Singapore
✦
European Union
▥
China
✣
South Korea
⌁
Australia
✚
United Kingdom
✦
Canada
▰
Japan
✣
Saudi Arabia
▥
India
✚
Brazil
●
US Federal Agencies, EOs, Guidance
▤
US States CA, CO, UT...
LOW REGULATORY PRESSURELower legal pressure Less prescriptive
HIGH REGULATORY PRESSUREHigher legal pressure More prescriptive
REGULATORY PRESSURE
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How to read it: jurisdictions are mapped by regulatory philosophy (vertical) and regulatory pressure (horizontal); placement reflects governance maturity and implementation architecture rather than solely the binding nature of obligations. Hover or tap any jurisdiction for its status and approach.
Source: “AI Governance in a Fragmented Regulatory Landscape” • IFK BioLiterate AI Ethics & Governance Article 1 Note: Placement reflects governance maturity and implementation architecture rather than solely the legal binding nature of obligations.
Despite divergent approaches, jurisdictions converge around core governance expectations: accountability, transparency, risk management, controllability and auditability.