{"id":14144,"date":"2026-03-30T03:39:02","date_gmt":"2026-03-30T07:39:02","guid":{"rendered":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=14144"},"modified":"2026-03-30T03:40:10","modified_gmt":"2026-03-30T07:40:10","slug":"you-must-address-these-4-concerns-to-deploy-predictive-ai","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/you-must-address-these-4-concerns-to-deploy-predictive-ai\/14144\/","title":{"rendered":"You Must Address These 4 Concerns To Deploy Predictive AI"},"content":{"rendered":"Predictive AI routinely fails to deploy, so data scientists are spearheading a movement to focus on its business value. But stakeholders need a better understanding.Eric Siegel (with Meta AI) Originally published in\u00a0Forbes Most\u00a0predictive AI\u00a0projects\u00a0fail to launch\u00a0into production. The number crunching is sound and the data scientist delivers a viable machine learning model \u2013 but stakeholder objections sadly preclude deployment. To better meet stakeholders where they are, ML professionals are spearheading\u00a0a movement to focus on predictive AI\u2019s business value. Rather than sticking with the traditional technical metrics that report on ML model performance, a proactive minority of data scientists <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/you-must-address-these-4-concerns-to-deploy-predictive-ai\/14144\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Originally published in\u00a0Forbes Most\u00a0predictive AI\u00a0projects\u00a0fail to launch\u00a0into production. The number crunching is sound and the data scientist delivers a viable machine learning model \u2013 but stakeholder objections sadly preclude deployment. To better meet stakeholders where they are, ML professionals are spearheading\u00a0a movement to focus on predictive AI\u2019s business value. Rather than sticking with the traditional [&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-14144","post","type-post","status-publish","format-standard","hentry","category-leading-stories"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14144","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=14144"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14144\/revisions"}],"predecessor-version":[{"id":14148,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14144\/revisions\/14148"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=14144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=14144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=14144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}