{"id":14018,"date":"2025-11-18T03:01:57","date_gmt":"2025-11-18T08:01:57","guid":{"rendered":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=14018"},"modified":"2025-11-18T03:01:57","modified_gmt":"2025-11-18T08:01:57","slug":"how-to-overcome-predictive-ais-everyday-failure","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/how-to-overcome-predictive-ais-everyday-failure\/14018\/","title":{"rendered":"How To Overcome Predictive AI&#8217;s Everyday Failure"},"content":{"rendered":"Originally published in\u00a0Forbes Executives know the importance of\u00a0predictive AI. As\u00a0Unilever CDO Morgan Vawter wrote, \u201cIts practical deployment represents the forefront of human progress: improving operations with science.\u201d But there\u2019s bad news for data scientists: Your predictive AI project will probably fail. Your customer probably won&#8217;t operationalize the machine learning model you deliver. They won&#8217;t use it, act on it or integrate it. Sadly, most models developed for deployment wind up on the shelf. But you probably already knew that. A plethora of\u00a0industry research and anecdotal wisdom has let that cat out of the bag. And yet what most <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/how-to-overcome-predictive-ais-everyday-failure\/14018\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Originally published in\u00a0Forbes Executives know the importance of\u00a0predictive AI. As\u00a0Unilever CDO Morgan Vawter wrote, \u201cIts practical deployment represents the forefront of human progress: improving operations with science.\u201d But there\u2019s bad news for data scientists: Your predictive AI project will probably fail. Your customer probably won&#8217;t operationalize the machine learning model you deliver. They won&#8217;t use [&hellip;]<\/p>\n","protected":false},"author":13468,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[3],"tags":[],"class_list":["post-14018","post","type-post","status-publish","format-standard","hentry","category-leading-stories"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14018","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/13468"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=14018"}],"version-history":[{"count":1,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14018\/revisions"}],"predecessor-version":[{"id":14019,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14018\/revisions\/14019"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=14018"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=14018"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=14018"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}