{"id":741482,"date":"2026-07-28T16:40:23","date_gmt":"2026-07-28T13:40:23","guid":{"rendered":"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/"},"modified":"2026-07-28T16:40:23","modified_gmt":"2026-07-28T13:40:23","slug":"most-enterprise-ai-spend-still-hasnt-left-the-lab","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/","title":{"rendered":"Most enterprise AI spend still hasn\u2019t left the lab"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_89 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6aee0e6a3b1a6\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #dd3333;color:#dd3333\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #dd3333;color:#dd3333\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6aee0e6a3b1a6\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#The_spend_isnt_wasted_its_parked\" >The spend isn\u2019t wasted, it\u2019s parked<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#Where_the_money_actually_goes_to_work\" >Where the money actually goes to work<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#Hyperscaler_bills_are_getting_more_scrutiny_not_less_trust\" >Hyperscaler bills are getting more scrutiny, not less trust<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#Inefficiency_has_a_paper_trail_and_it_rarely_starts_with_compute\" >Inefficiency has a paper trail, and it rarely starts with compute<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#The_gap_between_big_budgets_and_small_ones_isnt_really_about_budget\" >The gap between big budgets and small ones isn\u2019t really about budget<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/buradabiliyorum.com\/en\/most-enterprise-ai-spend-still-hasnt-left-the-lab\/#What_happens_over_the_next_year_and_a_half\" >What happens over the next year and a half<\/a><\/li><\/ul><\/nav><\/div>\n<p><img decoding=\"async\" src=\"https:\/\/media.thenextweb.com\/2026\/07\/enterprise-ai-spend-still-in-the-lab.avif\" \/><\/p>\n<div id=\"article-main-content\">\n<p>New research puts a hard number on something a lot of IT leaders already suspected. Most AI pilots never make it into production, and the spend behind them isn\u2019t dis<a href=\"https:\/\/buradabiliyorum.com\/en\/category\/download-scripts-themes-apps\/\" data-internallinksmanager029f6b8e52c=\"9\" title=\"Download Scripts &amp; Themes &amp; Apps\" target=\"_blank\" rel=\"noopener\">app<\/a>earing, it\u2019s just sitting in limbo.\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.linkedin.com\/in\/jbitz\/\" target=\"_blank\" rel=\"nofollow noopener\">Jon Bitz<\/a>, chief relationship officer and co-founder at\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.kloudstax.com\/\" target=\"_blank\" rel=\"nofollow noopener\">KloudStax<\/a>, says that limbo isn\u2019t the failure it looks like from the outside.<\/p>\n<p>The numbers keep landing in the same neighborhood no matter who\u2019s counting.\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.forrester.com\/blogs\/the-state-of-agentic-ai-in-2026-companies-are-chasing-few-are-catching\/\" target=\"_blank\" rel=\"nofollow noopener\">Forrester\u2019s latest research on agentic AI<\/a>\u00a0found that three-quarters of enterprise leaders say they\u2019re adopting it, but only a small minority have it running in anything beyond limited pilots.\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-02-26-lack-of-ai-ready-data-puts-ai-projects-at-risk\" target=\"_blank\" rel=\"nofollow noopener\">Gartner predicts<\/a>\u00a0that through 2026, organizations will abandon 60 percent of AI projects that aren\u2019t backed by AI-ready data and integration infrastructure. And\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.deloitte.com\/global\/en\/issues\/generative-ai\/state-of-ai-in-enterprise.html\" target=\"_blank\" rel=\"nofollow noopener\">Deloitte\u2019s own enterprise survey<\/a>\u00a0found that more than a third of companies are still using AI at a surface level, with little real change to how they actually work day to day.<\/p>\n<p>Put those together and a pattern starts to form. Enterprises are approving AI budgets faster than they\u2019re converting that spend into anything resembling a repeatable, working system, and the gap between the two has become one of the more uncomfortable open questions in\u00a0enterprise cloud\u00a0right now.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_spend_isnt_wasted_its_parked\"><\/span>The spend isn\u2019t wasted, it\u2019s parked<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Jon Bitz, who spends most of his time inside these budget conversations as a\u00a0Google Cloud partner, doesn\u2019t think the story is as bleak as the abandonment numbers make it sound.<\/p>\n<div class=\"inarticle-wrapper channel-cta\">\n<div class=\"ica-text\">\n<p class=\"ica-text__title\">TNW City Coworking space &#8211; Where your best work happens<\/p>\n<p>A workspace designed for growth, collaboration, and endless networking opportunities in the heart of tech.<\/p>\n<\/div>\n<\/div>\n<p>\u201c<em>A meaningful portion of AI cloud spend is still happening in pre-production, and that\u2019s not a bad thing,<\/em>\u201d Bitz said. \u201c<em>Testing, experimentation, and validation are all critical parts of adopting AI correctly. You need that phase to understand what works and what doesn\u2019t.<\/em>\u201d<\/p>\n<p>Where he does see a real problem is how long that phase tends to drag on without anyone stepping in to move it along. \u201c<em>In some cases, a large amount of what\u2019s being funded hasn\u2019t made its way into a stable, repeatable production workflow yet<\/em>,\u201d he said.<\/p>\n<p>His read on the fix isn\u2019t to cut the experimentation budget, which is the instinct a lot of finance teams reach for once the pilot numbers get uncomfortable. It\u2019s to get more deliberate about converting what the experimentation phase actually teaches an organization into something that ships. \u201c<em>Our goal isn\u2019t necessarily to reduce experimentation, it\u2019s to convert it<\/em>,\u201d Bitz said. \u201c<em>To take what\u2019s being learned and turn it into production systems, so spend shifts from testing into workloads that are actually driving value inside the business.<\/em>\u201d<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Where_the_money_actually_goes_to_work\"><\/span>Where the money actually goes to work<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Ask Bitz where cloud spend is already paying off and he points somewhere less flashy than most of the AI headlines from the last year. Not new model releases, not bigger context windows, just the unglamorous stuff that was already running a company before generative AI showed up.<\/p>\n<p>\u201c<em>Real value is showing up in core workflow automation, taking manual, time-intensive processes and turning them into production-ready systems,<\/em>\u201d he said, pointing to support operations, engineering output, and AI embedded directly into revenue-generating workflows as the places where it\u2019s landing.<\/p>\n<p>The misallocation, in his experience, tends to follow a familiar script. Teams chase a better model or spin up more GPUs because that part is easy, while the harder work of structuring data and defining workflows gets skipped. \u201c<em>If the data isn\u2019t structured and workflows aren\u2019t clearly defined, it becomes very difficult to move anything into production,<\/em>\u201d Bitz said.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Hyperscaler_bills_are_getting_more_scrutiny_not_less_trust\"><\/span>Hyperscaler bills are getting more scrutiny, not less trust<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>There\u2019s also been a louder conversation lately about whether enterprises are starting to push back on hyperscaler pricing itself, especially as\u00a0AI workloads\u00a0make monthly bills harder to predict.\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.flexera.com\/blog\/finops\/the-new-era-of-cloud-what-2026-data-tells-us-about-spend-scale-and-strategy\/\" target=\"_blank\" rel=\"nofollow noopener\">Flexera\u2019s 2026 State of the Cloud data<\/a>\u00a0backs that up from the finance side, with cost unpredictability tied to dynamic AI workloads showing up as one of the top hurdles enterprises report, and nearly half of large organizations now running a dedicated AI governance function to keep it in check. Bitz says that\u2019s not quite adding up to pushback on the platforms themselves in what he\u2019s hearing in practice.<\/p>\n<p>\u201c<em>We\u2019re starting to see more scrutiny, but not so much pushback on the hyperscalers themselves or the value of the solutions and platforms,<\/em>\u201d he said. \u201c<em>It\u2019s more about how spend is structured and managed.\u201d<\/em> The questions companies are actually asking tend to be narrower than a referendum on cloud pricing: what\u2019s actually driving the bill, what\u2019s tied to production versus pilots and proofs of concept, and where there\u2019s room to optimize.<\/p>\n<p>That scrutiny is nudging companies toward more opinionated architecture choices, serverless and managed services and workloads sized to what they actually need, along with tighter governance over who can spin up what. Partners are picking up more of that optimization work too. \u201c<em>It\u2019s less about challenging the price and more about asking how to use these platforms correctly,<\/em>\u201d Bitz said. \u201c<em>When the architecture, data, and usage patterns are right, the economics tend to follow.<\/em>\u201d<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Inefficiency_has_a_paper_trail_and_it_rarely_starts_with_compute\"><\/span>Inefficiency has a paper trail, and it rarely starts with compute<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>It\u2019s tempting to treat runaway AI cloud bills as a compute problem, since that\u2019s the line item everyone can see. Bitz says that\u2019s almost never where the real story is.<\/p>\n<p>\u201c<em>Compute is an easy thing to point to, but in most cases, inefficient spend is really a reflection of gaps in data, architecture, governance, and undefined workflows,<\/em>\u201d he said. Throwing a bigger model or more GPUs at a system that was never designed to support AI in the first place doesn\u2019t fix the underlying mess, it just makes the same inconsistency more expensive to run. As Bitz put it, AI isn\u2019t creating new problems inside an organization so much as it\u2019s amplifying the ones that were already there.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_gap_between_big_budgets_and_small_ones_isnt_really_about_budget\"><\/span>The gap between big budgets and small ones isn\u2019t really about budget<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>There\u2019s a separate worry running through a lot of mid-market conversations right now, which is that cloud pricing and infrastructure complexity are quietly widening the gap between companies that can afford to experiment with AI and companies that can\u2019t. Bitz thinks the gap is real but that people are pointing at the wrong cause.<\/p>\n<p>\u201c<em>Complexity plays a bigger role than just a budget gap between SMB, mid-market, and enterprise, although the barrier to entry is real,<\/em>\u201d he said. Larger organizations have room to absorb a few expensive misses along the way. Smaller ones don\u2019t get that same margin for error, so they end up needing to be more precise from the start rather than less ambitious. \u201c<em>The companies we see winning with AI aren\u2019t necessarily the ones spending the most, they\u2019re the ones implementing the cleanest systems around well-defined use cases<\/em>,\u201d Bitz said.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_happens_over_the_next_year_and_a_half\"><\/span>What happens over the next year and a half<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Bitz doesn\u2019t expect\u00a0AI spend\u00a0to slow down, but he does think the conversation inside enterprises is already shifting toward accountability rather than raw scale. He\u2019s watching for organizations moving proof-of-concept work onto real production-level KPIs, more attention paid to unit economics like\u00a0cost per output\u00a0or per workflow, engineering teams getting measured on the AI-driven output they produce rather than how much of the tooling they\u2019ve adopted, and more C-level visibility into what AI spend is actually buying.<\/p>\n<p>\u201c<em>AI adoption is still early for a lot of organizations, and as teams get more comfortable, the focus naturally shifts from \u2018are we using AI?\u2019 to \u2018is this actually working and driving value?<\/em>\u2018\u201d Bitz said. Over the next 12 to 18 months, he expects that shift to keep building, with spend continuing to grow but under a lot more pressure to show its work.<\/p>\n<\/p><\/div>\n<blockquote><p><strong><span style=\"color: #ff6600;\">If you liked the article, do not forget to share it with your friends. Follow us on\u00a0<span style=\"color: #ff0000;\"><a style=\"color: #ff0000;\" href=\"https:\/\/news.google.com\/publications\/CAAqBwgKMN63nwsw68G3Aw\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\"><strong>If you want to read more like this article, you can visit our <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/buradabiliyorum.com\/en\/category\/technology\/\" target=\"_blank\" >Technology category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<p><span style=\"color: black;\"><a style=\"color: #ff9900;\" href=\"https:\/\/thenextweb.com\/news\/most-enterprise-ai-spend-still-hasnt-left-the-lab\" target=\"_blank\" >Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>New research puts a hard number on something a lot of IT leaders already suspected. Most AI pilots never make it into production, and the spend behind them isn\u2019t disappearing, it\u2019s just sitting in limbo.\u00a0Jon Bitz, chief relationship officer and co-founder at\u00a0KloudStax, says that limbo isn\u2019t the failure it looks like from the outside. The&#8230;<\/p>\n","protected":false},"author":1,"featured_media":741483,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/media.thenextweb.com\/2026\/07\/enterprise-ai-spend-still-in-the-lab.avif","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[],"class_list":["post-741482","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/741482","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=741482"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/741482\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/741483"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=741482"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=741482"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=741482"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}