A study by MIT found that 95% of the generative AI pilots in companies do not show measurable impact on the results state. It does not measure that \u00abthe AI is not working\u00bb \u2014 it measures something more specific and more uncomfortable: almost no one yet knows how to distinguish, before building, which pilot will actually move the business forward and which will remain on demo forever.<\/p>\n\n\n\n
I\u2019ve been writing about the pieces of that problem for three weeks: who answers when an agent decides for the company, why Gartner predicts that more than 4 out of every 10 agent AI projects will be canceled, and what makes companies that do capture value different. I close the chapter with the question that, in retrospect, makes the other three unnecessary: have you already demonstrated value before starting to build?<\/p>\n\n\n\n
Most AI projects don't start with that question. They start with \u00abwe want an agent\u00bb or \u00ablet's try this tool,\u00bb and value is assumed rather than demonstrated. The result is predictable: something is built that works technically but doesn't move any metrics that the company cares about.<\/p>\n\n\n\n
Two of the most cited causes of failure are exactly this: a poorly defined business problem from the start, and a cost that grows unchecked because no one estimated it before building. Neither of these can be solved with better technology. They are solved before writing a single line of code.<\/p>\n\n\n\n
A Proof of Value is not a technical pilot or a demo. It is the business question answered with evidence, before committing budget: what specific value is going to be captured, with what metric it will be measured, and at what real\u2014not estimated\u2014cost can it be operated? The initiative that cannot answer those three questions with data is not ready to be built; it is ready to remain an assumption.<\/p>\n\n\n\n
This is not bureaucracy to slow down: it is what allows for quick and confident decision-making about which of the many AI ideas that arrive at any given direction deserve a budget, and which are discarded within weeks rather than months.<\/p>\n\n\n\n
The agent that acts without anyone deciding who answers, the project that is canceled without measuring the risk, the company that operates forever without scaling\u2014all three share the same root: the value was never rigorously demonstrated before building. Solving that is not the tenth priority of an AI strategy. It is the first question, before any other.<\/p>\n\n\n\n
Before approving your next AI project, the question is not how fashionable the tool is. It is whether you have already demonstrated, with data, that it is worth building it. A AI Value Discovery answers exactly that in two weeks, with a GO, CONDITIONAL or NO GO verdict at the initiative's discretion. <\/a><\/p>\n\n\n\n