{"id":210294,"date":"2026-05-07T11:52:00","date_gmt":"2026-05-07T15:52:00","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/05\/07\/the-inference-imperative-why-running-ai-is-harder-than-building-it\/"},"modified":"2026-05-07T12:10:10","modified_gmt":"2026-05-07T16:10:10","slug":"the-inference-imperative-why-running-ai-is-harder-than-building-it","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/05\/07\/the-inference-imperative-why-running-ai-is-harder-than-building-it\/","title":{"rendered":"The inference imperative: Why running AI is harder than building it"},"content":{"rendered":"<p><a href=\"https:\/\/www.cio.com\/article\/4168486\/the-inference-imperative-why-running-ai-is-harder-than-building-it.html\">The inference imperative: Why running AI is harder than building it<\/a><\/p>\n<p><a href=\"https:\/\/www.cio.com\/article\/4168486\/the-inference-imperative-why-running-ai-is-harder-than-building-it.html\">https:\/\/www.cio.com\/article\/4168486\/the-inference-imperative-why-running-ai-is-harder-than-building-it.html<\/a><\/p>\n<p>Publish Date: <a href=\"publish_date]\">2026-05-07 11:52:00<\/a><\/p>\n<p>Source Domain: <a href=\"www.cio.com\">www.cio.com<\/a><\/p>\n<ul>\n<li>\n<p><strong>Enterprises are advancing their AI capabilities<\/strong>: There has been a rapid expansion in access to AI models, tools, and platforms, lowering initial experimentation barriers.<\/p>\n<\/li>\n<li>\n<p><strong>Operationalizing AI involves significant challenges<\/strong>: The transition from AI development to scaling it at an enterprise level encounters obstacles due to enterprise complexities like fragmented data systems, legacy infrastructure, and distributed workflows not initially designed for AI execution.<\/p>\n<\/li>\n<li>\n<p><strong>Data challenges impede AI scale<\/strong>: The reliability of AI models depends on high-quality, context-rich, and consistent data. However, enterprise data often sprawls across multiple platforms without a unified structure, making it hard to produce dependable outputs and actions. <\/p>\n<\/li>\n<li>\n<p><strong>Scaling AI adds complexity<\/strong>: As organizations attempt to expand AI usage, they face increased complexities like data integration, governance, security, and compliance, which can slow progress and escalate operational risks.<\/p>\n<\/li>\n<li>\n<p><strong>Traditional operations models are insufficient<\/strong>: Traditional cloud and application management are reactive and rely on manual processes, which lack the continuous monitoring, iteration, and optimization needs of AI systems.<\/p>\n<\/li>\n<li>\n<p><strong>Integration of data, infrastructure, and operations is crucial<\/strong>: Successful AI organizations focus on how AI systems are run versus just built. They ensure a unified data environment, embedded governance, and real-time information access. <\/p>\n<\/li>\n<li>\n<p><strong>Automation is key to scalable AI operations<\/strong>: Automation in monitoring performance, maintaining data quality, and adapting to changing conditions aids in reducing manual efforts and improving consistency, thus operating AI systems more efficiently.<\/p>\n<\/li>\n<li>\n<p><strong>AI operating models must become more proactive and AI-native<\/strong>: The trend toward AI-first operating models allows organizations to reduce operational overhead, improve delivery speed, and better support innovation by embedding intelligence and automation into system design and operation.<\/p>\n<\/li>\n<\/ul>\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The inference imperative: Why running AI is harder than building it https:\/\/www.cio.com\/article\/4168486\/the-inference-imperative-why-running-ai-is-harder-than-building-it.html Publish Date: 2026-05-07&#8230;<\/p>\n","protected":false},"author":1,"featured_media":210295,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/www.cio.com\/wp-content\/uploads\/2026\/05\/4168486-0-61356000-1778169086-shutterstock_2284091345.jpg?quality=50&strip=all&w=1024","fifu_image_alt":"","footnotes":""},"categories":[14],"tags":[],"class_list":["post-210294","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/210294"}],"collection":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/comments?post=210294"}],"version-history":[{"count":1,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/210294\/revisions"}],"predecessor-version":[{"id":210296,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/210294\/revisions\/210296"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/media\/210295"}],"wp:attachment":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/media?parent=210294"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/categories?post=210294"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/tags?post=210294"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}