191 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.
Security briefings are warning that AI model weights are the new target, and that means CISOs and AI governance teams must merge their risk work by early 2028.
Cleverly disguised text inputs can trick enterprise chatbots into leaking sensitive data or executing unauthorized commands, turning a helpful assistant into a security liability.
Senior living facilities are rushing to adopt clinical AI tools without the validation, oversight, and impact assessments that healthcare learned to demand the hard way.
When algorithmic systems show discriminatory patterns, relying on market forces alone is not enough to satisfy legal and risk requirements.
New model releases bring new capabilities, but they also reset the baseline for what risk and governance teams need to monitor.
The Centre for Information Policy Leadership just hired a senior data and AI policy director. That is not an incident, but it is a signal about where AI privacy governance is heading, and most companies are not ready.
Enterprises are spending more on compliance paperwork while technical governance work falls, and the gap will leave models exposed.
A fake clip of Jimmy Kimmel spread online, and the failure wasn't the tech—it was the absence of a single control that could have stopped it.
Governance teams track privacy and fairness while attackers exploit robustness gaps that never appear in the risk taxonomy. That gap is the real story.
A local report on automated hiring bias shows why HR tools need fairness testing before they touch job applications.
Governance frameworks focus on fairness while security teams track active exploitation of infrastructure.
The AI governance lesson hiding inside a data-privacy headline — and what to do about it.
Governance teams are preparing for accidents when they should be preparing for targeted abuse using legitimate credentials.
A new diagnostic method called perturbation probing shows how easy it is to bypass LLM guardrails with slight text changes.
The EU AI Act is finally being used to stop a company that scraped billions of faces without consent.
Algorithmic discrimination is no longer an isolated HR issue, and governance teams need to trace how training data creates systemic bias before deployment.
Public incident feeds are dangerously quiet on model robustness and overreliance, creating a false sense of security.
The AI governance lesson hiding inside a fraud & deepfakes headline — and what to do about it.
AI agents inherit the access rights of the tools they invoke, creating a governance blind spot that will be exploited before the 2028 EU AI Act rules take effect.
Attack research on large language models has moved from demos to real campaigns, and most AI risk programs still treat prompt injection as a theoretical problem.
Governance frameworks treat AI agents as single tools, but when agents pass state across organizational boundaries, accountability splinters into something no compliance checklist can audit.
Behind the news: the AI governance gaps it exposes, and how to close them.
The absence of overreliance stories in the AI incident record is not proof the risk is rare. It is evidence that governance teams are burying the failures that would expose their own training programs.
A former Twitch employee is suing Amazon, alleging they used her private data to train a generative AI model without her permission.