Advancing the field of AI governance through rigorous research, empirical studies, and practical insights
Our research programme combines academic rigor with practical application, ensuring that AI governance practices are grounded in evidence rather than speculation.
Our framework synthesizes decades of academic research, industry practice, and regulatory evolution
Systematic evaluation of 100+ existing AI ethics frameworks, standards, and guidelines to identify best practices and gaps
Peer-reviewed research published in leading journals and institutions, ensuring credibility and rigor
Field-tested with organisations across sectors, refined through implementation experience and empirical outcomes
Advancing knowledge across critical domains of AI governance
Comparative analysis of AI governance approaches worldwide, identifying effective practices and implementation challenges across different organizational contexts and regulatory environments.
Developing evidence-based methodologies for identifying, assessing, and mitigating AI-related risks across technical, ethical, legal, and societal dimensions.
Investigating sources of bias in AI systems, developing fairness metrics, and creating practical interventions to ensure equitable outcomes across diverse populations.
Analyzing emerging AI regulations worldwide, providing guidance on compliance requirements, and bridging the gap between regulatory mandates and organizational practices.
Studying organizational readiness for responsible AI, developing maturity models, and identifying critical success factors for effective governance implementation.
Recent contributions to the AI governance knowledge base
Systematic review of 100+ AI ethics frameworks revealing critical implementation gaps and proposing an integrated meta-framework for practical governance.
Read Paper →Comprehensive guidance for organisations navigating EU AI Act compliance, including risk classification, documentation requirements, and implementation timelines.
Download Guide →Empirical study of 200+ SMEs examining AI governance adoption patterns, identifying resource constraints, and proposing scalable governance models.
Read Paper →Multi-case analysis of government agencies implementing AI governance, revealing common challenges and effective strategies for public sector contexts.
View Case Study →How our research influences policy, practice, and education
Our research cited in academic papers, policy documents, and industry reports
Organisations implementing our frameworks and recommendations
Global reach of our research and governance frameworks
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