Gartner said it without hesitation in mid-2025: more than 40% of agent AI projects will be canceled before the end of 2027. Not for lack of interest—on the contrary. It is unfiltered enthusiasm that is filling that graveyard. Last week...
Last week I wrote about the advice an agent gives and doesn’t ask who answers when they act. There’s a question before that too, and almost no one asks it either: how likely is it that this specific project will end up cancelled, and why?
The enthusiasm is not the problem. The lack of filtering is.
An agent project is canceled, almost always, for one of three reasons that have nothing to do with the model used. The first is cost: the token and infrastructure bill grows with usage, and what seemed cheap in the demo becomes a budget issue in production. In Mexico, 46% of the companies do not accurately understand the cost structure of their AI, and half of them already had to adjust a deployment when the cost exceeded the expected value (KPMG, Global AI Pulse Q2 2026).
The second is the risk without government: no one decided before building what data the agent can touch or what happens if it makes a mistake. The third — the most uncomfortable to admit — is buying something that promises more than what technology can do today. Gartner estimates that of the hundreds of providers that advertise as «AI agents,» only about 130 have a real offering. The rest are just chatbots with a new label.
What separates the surviving project from the one that is cancelled
Companies that do not end up in that statistic do not have better technology. They have a filter that they run before building, not after. At Scanda, we call this filter PoV Gate: each agent initiative is evaluated in three dimensions — does the pattern exist and can the team build it?, does the return justify the investment within a reasonable timeframe?, is the actual cost of operating it — tokens, infrastructure, maintenance— sustainable?— and receives a verdict of GO, CONDITIONAL or NO GO before committing budget.
That is not bureaucracy. It is the opposite: it allows you to say yes more quickly to the right projects, and no, with evidence, to those that would end up being cancelled anyway. 69% of companies believe that implementing government oversight for their AI will take more than a year (Deloitte); such a filter takes weeks, not years.
The question that matters more than the demo
Before approving the next agent, the demo isn’t what needs to be evaluated — any provider can make an agent look good in a room. What needs to be evaluated is whether someone has already run the real cost numbers, whether someone has already decided what happens if it fails, and whether what is being purchased actually exists or is just a promise with a new name.
Next step
An AI Value Discovery runs exactly that filter before the project exists: an AI opportunity map with a GO, CONDITIONAL, or NO GO verdict by initiative, within two weeks, before committing budget. Schedule yours
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