Insights
AI Governance Intelligence
Cited research and practitioner analysis on AI regulation, compliance methodology, and governance frameworks across APAC, EU, and global jurisdictions.
The Compliance Cost of Getting AI Governance Wrong: What the Data Actually Says
The Ponemon Institute's research consistently finds that non-compliance costs organisations 2.7 times more than maintaining active compliance programs. For AI systems, that multiplier is now compounding: regulatory fines, class action litigation, reputational losses, and board-level accountability exposure are arriving simultaneously. The organisations that dismissed AI governance as a future problem are finding it on this quarter's risk register.
8 cited sources
What Makes AIRA Different: Why AI Governance Needs a Different Kind of Platform
The global GRC software market is valued at over $50 billion. Most of it was built to manage yesterday's risk — SOC 2 checklists, annual ISO audits, quarterly board packs. AI governance is structurally different: the regulations are live, the risk is probabilistic, and the accountability chain now runs directly to the board. A platform designed for static compliance cannot govern dynamic AI.
6 cited sources
AI Governance Is Now a Board-Level Risk — Not an IT Problem
When the EU AI Act passed into law, it didn't assign liability to algorithms. It assigned liability to people — specifically, to the organisations that deploy AI systems in high-risk contexts. The legal question is no longer whether your AI works. It's whether your board can demonstrate it was governed.
3 cited sources
The Philippine AI Governance Landscape: What Every Company Needs to Know Before 2027
The Philippines is not waiting for global consensus on AI regulation. The National Privacy Commission's Advisory 2024-04 introduced mandatory AI impact assessments for systems that process personal data at scale. Organisations that treat this as an IT checklist are misreading the enforcement direction.
4 cited sources
EU AI Act vs. OECD AI Principles: One Framework to Know, One to Comply With
The OECD AI Principles, adopted by 47 countries, are the most widely cited reference for responsible AI — but they carry no enforcement power. The EU AI Act does. For organisations operating across jurisdictions, understanding which framework governs which obligation is the first step to a coherent compliance posture.
4 cited sources
How to Conduct an AI Impact Assessment That Holds Up Under Regulatory Scrutiny
An AI impact assessment is not a risk questionnaire. It is a documented, evidence-backed record of the decisions made before an AI system was deployed — decisions about data, about human oversight, about edge cases, and about what happens when the system is wrong. Regulators from Manila to Brussels are starting to ask for exactly that record.
4 cited sources
AIRA Editorial Standard
Every claim in AIRA's articles is sourced to a primary regulatory document, peer-reviewed study, or verified institutional report. We do not publish opinion as fact. Sources are linked inline and listed at the end of each article.