{"id":8240,"date":"2026-06-14T10:47:00","date_gmt":"2026-06-14T10:47:00","guid":{"rendered":"http:\/\/version1.thinktankdev.org.uk\/en-us\/?p=8240"},"modified":"2026-07-21T15:05:14","modified_gmt":"2026-07-21T15:05:14","slug":"define-the-problem-before-ai-solves-the-wrong-one","status":"publish","type":"post","link":"https:\/\/version1.thinktankdev.org.uk\/en-us\/blog\/define-the-problem-before-ai-solves-the-wrong-one\/","title":{"rendered":"Define the problem before AI solves the wrong one\u00a0"},"content":{"rendered":"

AI is making software delivery faster\u00a0which will\u00a0likely be\u00a0good news for organisations who want to ship products or deliver services to users.\u00a0\u00a0In the past, it has been the build phase that is usually the longest and most\u00a0complex part of any digital delivery.\u00a0\u00a0But as delivery speeds up, it is\u00a0exposing an organisational problem that the\u00a0IT\u00a0industry has\u00a0been tackling\u00a0for thirty years.\u00a0<\/p>\n

The Standish Group<\/a> has tracked software project outcomes since 1994. One finding has barely moved in three decades is that poor requirements cause 39% of project failures. Better tools, frameworks and methodologies over that time have not shifted the finding.\u00a0\u00a0Will AI shift it, or will it simply make the consequences arrive faster for the user?\u00a0<\/p>\n

Gartner<\/a> predicts that over 40% of agentic AI projects will be cancelled by the end of 2027 because organisations will be able to build the wrong thing faster than ever before.\u00a0<\/p>\n

Ensure\u00a0understanding\u00a0remains\u00a0front and centre of projects<\/b>\u00a0<\/h3>\n

Questions such as what do users need, how should a service flow end to end and what problem needs to be solved will determine whether a project succeeds.\u00a0\u00a0AI coding tools don\u2019t make these questions easier to answer but they do make it more urgent that we answer them well. \u00a0<\/p>\n

Previously when building something took weeks and we created it incrementally across sprints and the iteration created useful friction. Discovery happened to define the scope, enriched by research with users, and requirements were interrogated and refined because nobody wanted to waste time heading in the wrong direction.\u00a0<\/p>\n

The speed with which AI coding can happen now removes much of that friction. It\u2019s possible for requirements to become a working prototype in hours.\u00a0\u00a0In practice, that could mean a misunderstood requirement can become a built product before anyone has had time to question it.<\/p>\n

Gartner\u00a0describes AI generated code as\u00a0\u2018syntactically correct but lacking\u00a0awareness of broader system architecture and nuanced business rules. It builds what it is told, not what is needed.’\u00a0So\u00a0the teams that will get the most from AI-assisted development are the ones who are clearest about what they are asking it to build,\u00a0with\u00a0that\u00a0clarity\u00a0coming\u00a0from research, design, analysis\u00a0and mapping\u00a0the service end to end before a line of code is written. Those disciplines matter\u00a0even more now.\u00a0<\/p>\n

 <\/p>\n

Our engineering teams are building with AI tools and seeing real gains in delivery speed. Our Transformation Design Group works alongside them: user researchers talk to real users before assumptions become embedded in code, designers map journeys end to end, product managers hold the product vision and scope, BAs make requirements precise enough to build from and service designers make sure a change in one part of the service does not inadvertently break another. Together, they do the work that determines whether that development speed is pointed at the right problem.\u00a0<\/p>\n

Organisations\u00a0who invest\u00a0in AI\u00a0but also\u00a0invest in the people who know what to build before the AI starts\u00a0will be the ones\u00a0who\u00a0see the benefits for the services and products they deliver.\u00a0<\/p>\n

To find out how user-centred design can help you define the problem clearly before AI accelerates delivery, visit our User Centred Design page or talk to us.<\/h4>\n

User Centred Design<\/a> Talk to us<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

AI is making software delivery faster\u00a0which will\u00a0likely be\u00a0good news for organisations who want to ship products or deliver services to users.\u00a0\u00a0In the past, it has been the build phase that is usually the longest and most\u00a0complex part of any digital delivery.\u00a0\u00a0But as delivery speeds up, it is\u00a0exposing an organisational problem that the\u00a0IT\u00a0industry has\u00a0been tackling\u00a0for thirty […]<\/p>\n","protected":false},"author":8,"featured_media":8249,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[101],"tags":[],"industry":[],"class_list":["post-8240","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"translations":[{"blog_id":1,"post_id":8240,"name":"Europe","code":"EN-GB","hreflang":"en-gb","url":"https:\/\/version1.thinktankdev.org.uk\/blog\/define-the-problem-before-ai-solves-the-wrong-one\/","is_current":false},{"blog_id":13,"post_id":8240,"name":"Americas","code":"EN-US","hreflang":"en-us","url":"https:\/\/version1.thinktankdev.org.uk\/en-us\/blog\/define-the-problem-before-ai-solves-the-wrong-one\/","is_current":true}],"yoast_head":"\nDefine the problem before AI solves the wrong one\u00a0 | Version 1 (US)<\/title>\n<meta name=\"robots\" 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