Insight Hub
Our perspectives.
Perspectives and practical tools on AI governance, risk management, and enterprise-scale AI adoption. Grounded in global standards, regulatory frameworks, and real-world operating challenges.
Our insights focus on how organizations design control, make decisions, and scale AI responsibly: beyond principles and policy statements.
All publications
April 2026 · Standard Engagement
Our sensitivity analysis of the published AIVSS v0.8 scoring formula showed strong mitigations could score agentic systems below their CVSS baseline. We proposed the amendment for v1 that restores the risk floor.
April 2026 · Insight Report
A practitioner-level analysis of the three layers of enterprise AI integration tooling, the monitoring domains that complement them, and the architectural gap that remains ungoverned.
March 2026 · Insight Report
Why do 94% of organizations fail to scale AI? A source-ranked analysis of the 10 most consequential barriers to enterprise AI value, from data readiness to silent semantic drift.
March 2026 · Insight Report
Distilling the scientific consensus of the 2026 International AI Safety Report, this analysis provides an operational roadmap for GCC enterprises to bridge the evaluation gap through a four-layered, defense-in-depth governance architecture.
February 2026 · Article
AI risk is often treated as a technical issue. Risk propagates beyond systems through processes and decisions, becoming strategic, financial, or reputational exposure.
February 2026 · Article
Drawing on empirical insights from the MIT AI Risk Repository, this article examines how AI risks actually emerge in organizations and why effective governance requires proactive, lifecycle-based risk management.
February 2026 · Framework
A one-page operating model showing how mature organizations structure AI decision-making, risk control, and compliance assurance. Aligned with ISO 42001, 23894 and NIST AI RMF.
February 2026 · Article
As AI becomes embedded in core operations, organizations often rely on existing GRC frameworks. In practice, AI strains these assumptions and exposes gaps between formal compliance and effective control.
February 2026 · Article
Ethical AI defines values. Responsible AI defines action. This article breaks down the two and examines how each translates into governance structures, and why organizations need both.
January 2026 · Policy Engagement
MindXO's formal submission to the Monetary Authority of Singapore: proportionate application, a sandbox carve-out, organisational risk materiality thresholds, shadow AI discovery, and a 13-domain impact taxonomy.