<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Board Governance on carney.wiki</title><link>https://carney.wiki/tags/board-governance/</link><description>Recent content in Board Governance on carney.wiki</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Sun, 02 Nov 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://carney.wiki/tags/board-governance/index.xml" rel="self" type="application/rss+xml"/><item><title>What Boards Need to Know About AI Risk</title><link>https://carney.wiki/blog/what-boards-need-to-know-about-ai-risk/</link><pubDate>Sun, 02 Nov 2025 00:00:00 +0000</pubDate><guid>https://carney.wiki/blog/what-boards-need-to-know-about-ai-risk/</guid><description>Boards do not need to understand every AI model.
They do need to understand where AI creates business risk.
That is the important distinction.
AI is moving into customer interactions, employee workflows, software development, analytics, content production, fraud detection, security operations, and decision support. Some systems are low risk. Some can materially affect customers, employees, revenue, compliance, or reputation.
Board oversight should focus on the second group.
The question is not &amp;ldquo;Can the board explain how the model works?</description></item></channel></rss>