Metered pricing is the mechanism worth staring at. A vendor quote is a number that goes into a budget line before anyone signs, and a token bill is a number the buyer discovers afterwards, because the cost of a given task is typically not set in advance [3], with a fair number of builds dropped at the moment somebody totals up what has been consumed [4].
Run the base rate through the decision and it stops being a warning and becomes a threshold. More than 40% abandonment by the end of 2027 [2] leaves under 60% of projects delivering a working tool [1]; the spend on the ones that die buys learning and no software, so the expected cost of one surviving tool is the build budget divided by 0.6, or about 1.67 times that budget [2]. A build has to be quoted at sixty cents or less on the vendor's dollar just to be an even bet, before compliance and upkeep enter.
Devin Zito of Assurance Financial argues the other side: there is cost, he says, but nothing like hiring a full-time developer or a full-time development team to do the same work, provided the technology staff know enough to direct the model [6]. Fair, and aimed at a different comparison, or rather at the more flattering one, since the alternative to vibe coding a copilot is not hiring a team but buying somebody's copilot. Erik Eggers of Rocktop Technologies puts the residual plainly: the front-end cost of building collapsed, the cost of everything around the tool did not, and the rules of maintenance are unchanged [9].
Turnover sits on the same list of things that erase the saving [1], which for software assembled in prompts by one person is difficult to separate from the maintenance plan itself, and Zito, who also practises technology law in Baton Rouge, doubts that building changes many of the build-versus-buy compliance questions [7]. What the arithmetic does not touch is the capability: a team can now pull unstructured data off a single origination file or a whole portfolio and run analysis that optical character recognition never permitted [10][11].
Eggers expects token expenses to come down as users learn to control their modelling and providers make the models more efficient [8]. His forecast and Gartner's cost-surprise finding can both hold only if tokens consumed per task climb faster than the price per token falls, which is roughly what going agentic means.
This is probably wrong, but the useful reading of a 40% write-off rate is an option premium rather than a failure rate, and the two years or so between the study and its deadline [3] buys the option several times over. What would break it: if the abandoned projects die in week two, the sixty-cent threshold is far too harsh, since the write-off is small and fast; if they die after the tool is wired into origination and reviewed for compliance, 1.67x flatters it badly. The variable that decides which lender was right is how quickly a bad build gets killed.
