{"id":1013000000368,"date":"2026-09-17T15:52:06","date_gmt":"2026-09-17T15:52:06","guid":{"rendered":"https:\/\/www.version1.com\/en-us\/?p=1013000000368"},"modified":"2026-09-17T15:52:07","modified_gmt":"2026-09-17T15:52:07","slug":"the-next-stage-of-ai-adoption-turning-ai-investment-into-business-value","status":"publish","type":"post","link":"https:\/\/www.version1.com\/en-us\/the-next-stage-of-ai-adoption-turning-ai-investment-into-business-value\/","title":{"rendered":"The next stage of AI adoption: turning AI investment into business value"},"content":{"rendered":"\n
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When organisations begin their AI<\/a> adoption journey, they often start in the wrong place. Instead of leadership asking themselves, “How do we adopt AI?”, the real consideration should centre around a simpler, more fundamental question: “how do we locate the business value”.<\/p>\n

This distinction separates successful AI implementations from those that unnecessarily consume time and resources without meaningful outcomes. AI is not the answer to every business problem. It is a tool that can solve specific problems exceptionally well, if deployed with clarity of purpose and disciplined thinking.<\/p>\n <\/div>\n \n <\/div>\n <\/div>\n<\/section>\n\n\n\n

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The value-led approach<\/h2>\n \n
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The traditional approach to technology adoption has relied on following a structured methodology: scope the project, assign resources, execute the plan. Many organisations assume AI adoption follows the same playbook. It does, but with a critical caveat. The starting point is not the technology. The starting point is identifying where genuine business value can be unlocked.<\/p>\n

This begins with understanding your value streams. Consider a purchase-to-pay process. Within that stream, multiple steps exist where time is consumed, complexity is unnecessary, and business value is being lost. The opportunity lies in identifying which steps are genuinely redundant, which are unnecessarily complex, and which could be reimagined using the tools now available, including AI.<\/p>\n

The most powerful implementations do not automate existing processes blindly. Instead, they question the process itself. They ask: Why is this step being performed this way? Are there system configurations or business rules that could be adjusted? Could this step be eliminated entirely rather than automated? Only when these questions have been addressed can you confidently identify where AI delivers genuine value.<\/p>\n <\/div>\n \n <\/div>\n <\/div>\n<\/section>\n\n\n\n

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Five factors that determine success<\/h2>\n \n
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Drawing on our experience of guiding clients through AI adoption, we have identified five factors that consistently underpin success. These are not sequential steps, nor are they universally weighted. The emphasis will shift depending on your organisational context. What remains constant is that overlooking any of these five creates genuine risk to achieving the defined outcomes.<\/p>\n <\/div>\n \n <\/div>\n <\/div>\n<\/section>\n\n\n\n

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1. Business value and business use cases<\/h2>\n \n

This cannot be separated from everything that follows. Every AI initiative must have a documented business case that articulates the specific, measurable benefit. This is not aspirational language about efficiency gains or market advantage. It is specific quantification, such as:<\/p>\n