316 free articles on AI governance and AI risk management: EU AI Act, NIST AI RMF, ISO 42001, incidents, deadlines and practical controls. New posts daily. Subscribe by RSS.
China’s 2026 AI regulatory guidance outlines enforcement priorities and compliance steps, affecting how global companies manage AI risk in China.
This week's posts reveal how current governance frameworks are failing to address the dynamic nature of AI systems across healthcare, finance, and consumer applications.
The dramatic drop in compliance incident coverage is not reduced risk—it's a reporting artifact created by the EU AI Act.
Nine posts on rules without timelines, filters that miss multi-agent loops, and documentation that stands in for real controls.
Recent legislative rollbacks leave AI discrimination laws in a state of flux, creating compliance gaps for organizations deploying automated decision systems.
As AI systems gain the ability to read and act on personal records, privacy teams face a brand new category of data exposure risk.
Organizations are focusing on governance documentation rather than actual risk mitigation, creating a false sense of security.
Prompt injection attacks succeed because large language models follow instructions, not because the underlying code crashed.
How AI voice cloning exposes the gap between consumer trust and enterprise security in fraud prevention.
The One Big Beautiful Bill Act carried a provision to stop states from regulating AI for a decade, and the governance risk sits in the gap between federal inaction and state enforcement.
Traditional annual model validation cycles cannot keep pace with the continuous deployment loops of AI agent tool invocation.
When AI systems win over vulnerable users by acting like close friends, the lines around consent, data collection, and personal privacy blur in ways standard governance fails to catch.
Governance teams are funding policy artifacts while the attack surface their own telemetry shows is tool invocation and model evasion.
A real security story, decoded for AI governance — and the concrete controls it points to.
OSFI's model risk guideline imports an annual, pre-deployment validation cadence onto AI systems that change behaviour between sign-offs, and the gap will surface in Canadian banks' incident counts before it surfaces in their audits.
A real data-privacy story, decoded for AI risk management — and the concrete controls it points to.
Single-point output filters cannot stop distributed generation.
What our scouts found across 53,672 open AI agents and MCP servers in the week of 12 October 2026 to 18 October 2026: who is doing the basics well, what we held back, and how the ecosystem measures up.
A look at this week's AI risk news, from silent overreliance to silent bank fraud.
A look at the week's biggest shifts in AI risk, from the EU's first active enforcement cases to silent risks like human overreliance and agentic fraud.
A recent Nature scoping review confirms that bias in large medical AI models remains widespread, posing severe risks for patient care.
When AI labs support reporting rules but dodge timelines, governance teams are left guessing how fast they must act.
Recent research highlights that large language models can get permanently stuck on fabricated facts, creating severe liability for businesses.
When enforcement agencies extend investigation windows, organizations face prolonged uncertainty and mounting legal exposure.