{"id":8790,"date":"2026-08-01T10:53:28","date_gmt":"2026-08-01T02:53:28","guid":{"rendered":"https:\/\/moresourcing.com\/ai-and-it-teams-often-clash-but-they-dont-have-to\/"},"modified":"2026-08-01T10:53:28","modified_gmt":"2026-08-01T02:53:28","slug":"ai-and-it-teams-often-clash-but-they-dont-have-to","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/en\/ai-and-it-teams-often-clash-but-they-dont-have-to\/","title":{"rendered":"AI and IT Teams Often Clash. But They Don\u2019t Have To."},"content":{"rendered":"<p><\/p>\n<div>\n<p class=\"Paragraph-module-scss-module__UwInRW__text\" data-first-paragraph=\"true\">In many organizations, IT and AI\u00a0are bundled together under the vague label of \u201ctechnology.\u201d Yet the two groups often have fundamentally different perspectives. <a href=\"https:\/\/www.researchgate.net\/publication\/236973378_IT_Governance_How_Top_Performers_Manage_IT_Decision_Rights_for_Superior_Results\" class=\"ContentLink-module-scss-module__qKDjGa__anchor\">IT\u00a0teams seek control, standardization, and risk reduction<\/a>; <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s43681-022-00143-x?utm_source=chatgpt.com\" class=\"ContentLink-module-scss-module__qKDjGa__anchor\">AI teams seek experimentation, flexibility and rapid learning<\/a>. \u00a0Left unmanaged, these competing priorities can result in the groups unintentionally sabotaging each other\u2019s efforts.<\/p>\n<\/div>\n<p><script async=\"\" defer=\"\" crossorigin=\"anonymous\" src=\"https:\/\/connect.facebook.net\/en_US\/sdk.js#version=v19.2&amp;appId=1761258887507575&amp;xfbml=false&amp;status=true\"><\/script><\/p>\n<p>#Teams #Clash #Dont<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In many organizations, IT and AI\u00a0are bundled together under the vague label of \u201ctechnology.\u201d Yet the two groups often have fundamentally different perspectives. IT\u00a0teams seek control, standardization, and risk reduction; AI teams seek experimentation, flexibility and rapid learning. \u00a0Left unmanaged, these competing priorities can result in the groups unintentionally sabotaging each other\u2019s efforts. #Teams #Clash [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":8791,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[9],"tags":[],"class_list":["post-8790","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-management"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.7.1 (Yoast SEO v25.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI and IT Teams Often Clash. But They Don\u2019t Have To. - MORE SOURCING LTD<\/title>\n<meta name=\"description\" content=\"The arrival of AI has exposed a growing organizational fault line. Although AI and IT are often grouped together as \u201ctechnology,\u201d they typically operate with very different priorities: IT emphasizes control, standardization, and risk reduction, while AI depends on experimentation, flexibility, and rapid learning. Through three case studies, the authors show how these competing logics create conflict over data, capabilities, and infrastructure, slowing AI adoption and limiting business value. Organizations that succeed do not force one function to dominate the other. Instead, they clarify roles, expand governance to encompass new forms of data, align AI ambitions with IT readiness, and establish shared accountability for business outcomes. The result is less friction, stronger collaboration, and greater competitive advantage from both AI and IT.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/moresourcing.com\/en\/ai-and-it-teams-often-clash-but-they-dont-have-to\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI and IT Teams Often Clash. But They Don\u2019t Have To.\" \/>\n<meta property=\"og:description\" content=\"The arrival of AI has exposed a growing organizational fault line. Although AI and IT are often grouped together as \u201ctechnology,\u201d they typically operate with very different priorities: IT emphasizes control, standardization, and risk reduction, while AI depends on experimentation, flexibility, and rapid learning. Through three case studies, the authors show how these competing logics create conflict over data, capabilities, and infrastructure, slowing AI adoption and limiting business value. Organizations that succeed do not force one function to dominate the other. Instead, they clarify roles, expand governance to encompass new forms of data, align AI ambitions with IT readiness, and establish shared accountability for business outcomes. 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