{"id":21,"date":"2026-02-19T16:00:00","date_gmt":"2026-02-19T21:00:00","guid":{"rendered":"https:\/\/www.nestorsoftware.com\/ai-in-procurement-the-honest-version\/"},"modified":"2026-02-19T16:00:00","modified_gmt":"2026-02-19T21:00:00","slug":"ai-in-procurement-the-honest-version","status":"publish","type":"post","link":"https:\/\/www.nestorsoftware.com\/?p=21","title":{"rendered":"AI in procurement: the honest version"},"content":{"rendered":"<p>&#8216;AI for procurement&#8217; covers a lot of ground. Some of it is real; some is a rebrand of features that existed before the term became fashionable. Worth separating the two.<\/p>\n<h2>Where AI is already useful<\/h2>\n<ul>\n<li><strong>Spend classification.<\/strong> Mapping a messy general-ledger transaction list to a clean category taxonomy is exactly the kind of fuzzy, pattern-matching task ML handles well. The category accuracy on first pass is now typically above 90%, which beats the manual baseline and beats rules-based systems that have to be rewritten every time the ERP changes.<\/li>\n<li><strong>Anomaly detection in supplier behavior.<\/strong> Bid patterns, lead-time slippage, quality incidents \u2014 surface them before they show up as problems.<\/li>\n<li><strong>Negotiation strategy suggestions.<\/strong> Pattern-recognition across historical events: &#8216;in the last three auctions for this category, the lowest bidder was set within the first 12 minutes. Consider shortening the event window.&#8217;<\/li>\n<\/ul>\n<h2>Where it&#8217;s still mostly marketing<\/h2>\n<ul>\n<li><strong>&#8216;AI-negotiated&#8217; contracts where the model writes back to the supplier.<\/strong> These exist in narrow, tactical categories. They do not work for anything strategic.<\/li>\n<li><strong>Predictive should-cost.<\/strong> Genuine should-cost modeling is engineering work \u2014 material specs, process flow, labor rates. A model trained on past prices is just predicting past prices.<\/li>\n<\/ul>\n<h2>The honest framing<\/h2>\n<p>The valuable AI in procurement looks like a co-pilot, not an autopilot. It surfaces patterns, drafts options, flags anomalies \u2014 and leaves the negotiating to the negotiator. Anyone selling the autopilot version either has a very narrow use case in mind, or isn&#8217;t being precise.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Past the hype: where AI genuinely helps a sourcing team today, where it doesn&#8217;t, and how to tell the difference.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-21","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=\/wp\/v2\/posts\/21","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=21"}],"version-history":[{"count":0,"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=\/wp\/v2\/posts\/21\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=21"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=21"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.nestorsoftware.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=21"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}