<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ai-Consulting on AI For Human Expertise</title><link>https://aiforhumanexpertise.com/tags/ai-consulting/</link><description>Recent content in Ai-Consulting on AI For Human Expertise</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Mon, 09 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://aiforhumanexpertise.com/tags/ai-consulting/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Doesn't Just Miss Tacit Knowledge. It Can Destroy It.</title><link>https://aiforhumanexpertise.com/blog/welcome/</link><pubDate>Mon, 09 Feb 2026 00:00:00 +0000</pubDate><guid>https://aiforhumanexpertise.com/blog/welcome/</guid><description>&lt;h2 id="the-standard-framing-gets-something-important-wrong"&gt;The Standard Framing Gets Something Important Wrong&lt;/h2&gt;
&lt;p&gt;The dominant logic behind most AI adoption is straightforward: find the task, automate the task, reduce the cost or time. It is a reasonable starting point. The problem is what it misses.&lt;/p&gt;
&lt;p&gt;Tasks do not exist in isolation. Behind most of the tasks worth automating is a body of expertise: judgement built over years, pattern recognition that operates faster than it can be explained, contextual awareness that no process document has ever fully captured. This is tacit knowledge, and it is almost never accounted for in the standard AI adoption model.&lt;/p&gt;</description></item></channel></rss>