{"id":92558,"date":"2025-10-21T17:59:07","date_gmt":"2025-10-21T17:59:07","guid":{"rendered":"https:\/\/www.newsbeep.com\/nz\/92558\/"},"modified":"2025-10-21T17:59:07","modified_gmt":"2025-10-21T17:59:07","slug":"why-cloud-and-ai-projects-take-longer-and-how-to-fix-the-holdups","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/nz\/92558\/","title":{"rendered":"Why cloud and AI projects take longer and how to fix the holdups"},"content":{"rendered":"

No. 2 problem: Unrealistic expectations lead to problematic requirements<\/p>\n

Early planning and business case validation show that the requirements set for the project can\u2019t be met, which then requires a period of redefinition before real work can start. This situation \u2013 reported by 69% of enterprises \u2013 leads to an obvious question: Is it the requirements or the project that\u2019s the problem? Enterprises who cite this issue say it\u2019s the former, and that it\u2019s how the requirements are set that\u2019s usually the cause.<\/p>\n

In the case of the cloud, the problem is that senior management thinks that the cloud is always cheaper, that you can always cut costs by moving to the cloud. This is despite the recent stories on \u201crepatriation,\u201d or moving cloud applications back into the data center<\/a>. In the case of cloud projects, most enterprise IT organizations now understand how to assess a cloud project for cost\/benefit, so most of the cases where impossible cost savings are promised are caught in the planning phase.<\/p>\n

For AI, both senior management and line department management have high expectations with respect to the technology, and in the latter case may also have some experience with AI in the form of as-a-service generative AI models available online. About a quarter of these proposals quickly run afoul of governance policies because of problems with data security, and half of this group dies at this point. For the remaining proposals, there is a whole set of problems that emerge.<\/p>\n

Most enterprises admit that they really don\u2019t understand what AI can do, which obviously makes it hard to frame a realistic AI project. The biggest gap identified is between an AI business goal and a specific path leading to it. One CIO calls the projects offered by user organizations as \u201cinvitations to AI fishing trips\u201d because the goal is usually set in business terms (\u201cimprove sales\/competitive position\u201d or \u201creduce inventory cost\u201d), and these would actually require a project simply to identify how the stated goal could be achieved. From that, it would be possible to frame an actual project to implement a strategy.<\/p>\n

Why doesn\u2019t this happen with traditional technology? According to enterprises, the big reason is that line organizations can experiment with AI, and draw conclusions about its benefit to them, without any IT involvement at all. In the past, with non-AI technologies, line departments tended to work with IT just to learn what could be done. \u201cEarly partnership with IT makes a big difference,\u201d one IT professional with AI skills noted.<\/p>\n

This particular problem, though, happens a lot less often for enterprise IT leaders who have a strategic vendor partner who has practical AI experience. A \u201cstrategic vendor\u201d is usually one that has broad enterprise engagement and credibility. Combine that with AI skills, and you have a combination that can meld business and technology, which overcomes the problem of translating business goals to steps that can be implemented.<\/p>\n","protected":false},"excerpt":{"rendered":"No. 2 problem: Unrealistic expectations lead to problematic requirements Early planning and business case validation show that the…\n","protected":false},"author":2,"featured_media":92559,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[371,111,139,69,145],"class_list":{"0":"post-92558","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-computing","8":"tag-computing","9":"tag-new-zealand","10":"tag-newzealand","11":"tag-nz","12":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/92558","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/comments?post=92558"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/92558\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media\/92559"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media?parent=92558"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/categories?post=92558"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/tags?post=92558"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}