GLOBAL AI POLICY ANALYSIS • 2025–2026

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

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

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.