{"id":16262,"date":"2026-07-20T00:00:38","date_gmt":"2026-07-20T00:00:38","guid":{"rendered":"https:\/\/hostnoc-revamp.branex.org\/blog\/?p=16262"},"modified":"2026-07-17T04:41:41","modified_gmt":"2026-07-17T04:41:41","slug":"ai-inference-is-moving-to-private-cloud","status":"publish","type":"post","link":"https:\/\/hostnoc-revamp.branex.org\/blog\/ai-inference-is-moving-to-private-cloud\/","title":{"rendered":"7 Reasons Why AI Inference Is Moving to Private Cloud"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Enterprises are moving beyond AI experimentation and into large-scale production deployments, a significant shift is taking place in cloud strategy. Organizations that initially relied on public cloud platforms for AI development are increasingly moving AI inference workloads to private cloud environments.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to a <\/span><a href=\"https:\/\/url.usb.m.mimecastprotect.com\/s\/-HiQC4Wr9rhLzljAtOfjc4S-Yv?domain=vmware.com\" target=\"_blank\" rel=\"nofollow noopener\"><span style=\"font-weight: 400;\">survey<\/span><\/a><span style=\"font-weight: 400;\"> of 1,800 senior IT decision-makers conducted by Radius Tech on behalf of Broadcom, private cloud adoption for AI workloads is accelerating. The study found that only 41% of enterprises are now using public clouds for inference workloads, down from 56% a year earlier, while private cloud usage for AI inference has risen to 56%.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Broadcom describes this as an &#8220;<\/span><b>AI tipping point<\/b><span style=\"font-weight: 400;\">&#8221; that is reshaping enterprise infrastructure decisions.<\/span><\/p>\n<h2>7 Reasons Why AI Inference Is Moving to Private Cloud<\/h2>\n<p>Here are seven reasons why AI inference is moving to private cloud.<\/p>\n<h3><b>1. Security and Compliance Have Become the Top Priority<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Cloud costs dominate discussions about AI deployment, the survey reveals that security and compliance are the most influential factors driving infrastructure decisions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">When asked what most determines where workloads run:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">32% selected security and compliance<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">15% chose data sovereignty and control<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">14% cited performance and latency<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">14% pointed to integration with existing systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">12% selected cost<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">12% selected speed of deployment and scalability<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">These findings show that organizations increasingly prioritize risk management and governance over pure cost considerations.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As AI systems gain access to sensitive enterprise data, organizations want greater oversight of how information is stored, processed, and protected.<\/span><\/p>\n<h3><b>2. Data Sovereignty Requirements Are Growing<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Data sovereignty has emerged as a major concern, particularly for organizations operating outside the United States.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The survey found that 15% of enterprises consider data sovereignty and control the most important factor in workload placement decisions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to ABI Research analyst Michela Menting:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;With the largest public cloud providers being US-based, there is concern in the rest of the world for data protection that meets local regulations.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As governments introduce stricter data residency and privacy requirements, enterprises are seeking environments where they can maintain greater control over where data resides and how it is processed.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Private clouds often provide clearer governance frameworks for meeting these obligations.<\/span><\/p>\n<h3><b>3. AI Inference Needs to Be Closer to Enterprise Data<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">AI training and AI inference have different infrastructure requirements.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Many organizations initially used public clouds to train models and run pilot projects. However, production inference workloads often need direct access to enterprise data sources.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Prashanth Shenoy, CMO and Vice President of Marketing for VMware Cloud Foundation at Broadcom, explained:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;Now that the majority of large-scale enterprise customers are done doing that, they want the models to be closer to where the data is and where the data is generated.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">He added:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;And that is in their own on-premise private cloud environment.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Keeping AI models close to operational data can reduce complexity, improve governance, and streamline business processes.<\/span><\/p>\n<h3><b>4. Predictable AI Costs Matter More Than Ever<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Generative AI and agentic AI applications are introducing new infrastructure challenges.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to the survey, 62% of IT leaders are either &#8220;very&#8221; or &#8220;extremely&#8221; concerned about generative AI and agentic AI infrastructure costs.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Inference workloads can run continuously and at massive scale, creating unpredictable consumption patterns in public cloud environments. Agentic AI systems can further amplify costs by increasing interactions with large language models.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/hostnoc-revamp.branex.org\/blog\/7-reasons-why-private-cloud-are-making-a-comeback\/\">Private cloud<\/a> environments offer organizations more predictable spending models, helping them avoid unexpected cost overruns while maintaining performance.<\/span><\/p>\n<h3><b>5. Enterprises Are Repatriating Workloads from Public Clouds<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The movement toward private infrastructure is not limited to AI.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The study found that:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">50% of enterprises have already repatriated some workloads from public clouds<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">This is up from 35% in 2025<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Another 33% are actively considering repatriation<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">At the same time, 72% of enterprises plan to increase private cloud spending over the next three years, compared with 51% in the previous year&#8217;s survey.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These figures suggest a broader reevaluation of cloud strategies as organizations seek better alignment between performance, governance, and economics.<\/span><\/p>\n<h3><b>6. Performance and Latency Requirements Are Increasing<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">AI applications are becoming more integrated into mission-critical business processes where speed matters.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The survey found that 14% of respondents consider performance and latency the most important factor in determining workload placement.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Inference workloads often require rapid access to large datasets, specialized accelerators, and low-latency networking. Hosting these workloads within private cloud environments can reduce delays associated with moving data between enterprise systems and external cloud services.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As AI becomes embedded in customer experiences, operational systems, and real-time decision-making processes, latency optimization becomes increasingly important.<\/span><\/p>\n<h3><b>7. Enterprises Want Greater Control Over AI Infrastructure<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Control remains one of the strongest arguments for private cloud adoption.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to the survey, enterprises are highly concerned about data protection, privacy, security, and operational control. AI systems introduce additional governance requirements because they process large datasets, rely on expensive accelerators, and require specialized networking and security controls.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dell&#8217;Oro Group analyst Mauricio Sanchez summarized the changing landscape:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;The old assumption that every workload eventually moves to public cloud has broken down.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">He further noted:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;If a company is running steady AI inference against sensitive data, wants more control over where data and models live, or needs predictable economics, a private cloud can look much better than it did a few years ago.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For many organizations, private clouds now offer the combination of governance, visibility, and operational control needed to support enterprise AI at scale.<\/span><\/p>\n<h2><b>The Bottom Line<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The enterprise AI market is entering a new phase. While public clouds remain valuable for AI experimentation, training, and highly variable workloads, organizations are increasingly choosing private clouds for production AI inference.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The numbers tell the story:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Public cloud usage for AI inference fell from 56% to 41% year over year.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Private cloud usage for AI inference reached 56%.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">72% of enterprises plan to increase private cloud spending.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">62% are highly concerned about AI infrastructure costs.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">50% have already repatriated workloads from public clouds.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Security, compliance, data sovereignty, performance, and operational control\u2014not just cost\u2014are driving this shift. As AI becomes central to business operations, enterprises are finding that private cloud environments provide the governance, predictability, and proximity to data required for long-term success.<\/span><\/p>\n<p>Why do you think AI inference is moving to private cloud? Share it with us in the comments section below.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Enterprises are moving beyond AI experimentation and into large-scale production deployments, a significant shift is taking place in cloud strategy. Organizations that initially relied on public<span class=\"excerpt-hellip\"> [\u2026]<\/span><\/p>\n","protected":false},"author":3,"featured_media":16263,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[236],"tags":[],"class_list":["post-16262","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cloud-hosting"],"acf":[],"_links":{"self":[{"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/posts\/16262","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/comments?post=16262"}],"version-history":[{"count":1,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/posts\/16262\/revisions"}],"predecessor-version":[{"id":16264,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/posts\/16262\/revisions\/16264"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/media\/16263"}],"wp:attachment":[{"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/media?parent=16262"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/categories?post=16262"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hostnoc-revamp.branex.org\/blog\/wp-json\/wp\/v2\/tags?post=16262"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}