A 9-Pillar AI Governance Framework: Evidence-Based, Implementation-Ready
A comprehensive, practical system for operationalising responsible AI governance. Moving organisations beyond high-level principles to concrete, measurable actions.
Built on over 30 years of research and an evaluation of more than 100 existing frameworks, our model synthesises global best practices into a single, coherent system.
Designed for implementation, not just theory. The framework provides clear steps, assessment tools, and certification pathways to guide your journey.
Aligned with major global regulations and standards, including the EU AI Act, NIST AI RMF, and ISO/IEC 42001, providing a clear path to compliance.
Our approach is built on a foundation of deep research and a commitment to practical application. We provide the tools and knowledge to build trust, mitigate risk, and unlock the full potential of responsible AI.
Synthesising decades of academic and industry work
A comprehensive meta-analysis of global standards
A single, unified framework for holistic governance
Three guiding principles that define our approach to AI governance.
We provide flexible, adaptable tools that fit your organisation's context, size, and maturity level.
Our focus is on providing concrete, actionable steps that lead to measurable improvements in AI governance.
We aim to build genuine organisational capacity and a culture of responsibility, not just a checklist-driven approach to compliance.
Nine interdependent pillars that provide a holistic approach to AI governance. Each pillar represents a critical domain of inquiry and action.
| Pillar | Description |
|---|---|
1 Accountability & Governance | Establishes clear lines of responsibility and oversight for AI systems throughout their lifecycle. |
2 Fairness & Non-Discrimination | Implements processes to identify, measure, and mitigate unfair bias in AI models and data. |
3 Transparency & Explainability | Ensures that AI systems and their decisions can be understood by relevant stakeholders. |
4 Data Privacy & Security | Protects personal and sensitive data through robust data governance and security protocols. |
5 Reliability & Safety | Guarantees that AI systems perform as intended, are resilient to failure, and operate safely. |
6 Human Oversight & Control | Ensures meaningful human control is in place to prevent and correct AI-driven errors or harms. |
7 Societal & Environmental Well-being | Assesses and addresses the broader impacts of AI systems on society and the environment. |
8 Legal & Regulatory Compliance | Maps and manages compliance with the complex landscape of global AI laws and regulations. |
9 Stakeholder Engagement | Creates formal channels for communicating with and involving all parties affected by AI systems. |
We guide organisations through a structured journey to operationalise AI governance. Timeline ranges from 30 days for initial assessment to 12 months for comprehensive integration.
Use our online tools to benchmark your current AI governance maturity and identify critical gaps.
Develop a tailored, prioritised roadmap based on your assessment results and organisational goals.
Deploy targeted interventions, policies, and controls using our library of templates and best practices.
Establish ongoing monitoring, reporting, and continuous improvement cycles to ensure lasting governance.
Our framework is designed to provide value to a wide range of organisations and individuals.
| Sector | Key Benefit |
|---|---|
| Enterprises | Streamline compliance, mitigate enterprise-level risks, and build consumer trust. |
| SMEs | Access affordable, scalable governance tools to compete responsibly and win business. |
| Public Sector | Ensure public services are delivered ethically, equitably, and with full accountability. |
| Third Sector | Align AI-driven missions with core values and demonstrate impact to funders. |
| Individuals | Gain accredited certifications to build a professional career in AI ethics and governance. |
Ready to move from principles to practice? Choose the path that's right for you.
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