<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Model Governance on carney.wiki</title><link>https://carney.wiki/tags/model-governance/</link><description>Recent content in Model Governance on carney.wiki</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Tue, 20 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://carney.wiki/tags/model-governance/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Risk Is a Business Risk, Not Just a Technical One</title><link>https://carney.wiki/blog/ai-risk-is-a-business-risk-not-just-a-technical-one/</link><pubDate>Tue, 20 Jan 2026 00:00:00 +0000</pubDate><guid>https://carney.wiki/blog/ai-risk-is-a-business-risk-not-just-a-technical-one/</guid><description>AI risk is business risk.
That sounds obvious until you look at how most companies still manage it.
Too often, AI risk gets pushed into the technical corner. The security team worries about exposure. The data team worries about model performance. Legal gets pulled in late. The board gets a sanitized update after the pilot has already become operational.
That is backwards.
If an AI system influences customers, employees, financial outcomes, operational decisions, or regulated processes, the risk is not contained inside the model.</description></item></channel></rss>