No one ever wants to give a technology team a blank check. Yet for many chief financial officers, that’s exactly what they were asked to do in the early rush to embrace AI. Now, after one-too-many surprise bills, finding a way to control costs has become an imperative.
It’s a simmering issue in banks, where technology budgets are already under pressure from competing demands ranging from legacy IT modernization to cybersecurity. Some of the greatest hopes for productivity improvements are pinned on agentic AI, which can tackle complex tasks autonomously, but are inherently difficult to budget for as the amount of computing power each task consumes can be unpredictable.
“I actually don’t think anybody in the organization has a good handle on it - if I am going to do XYZ, what is going to be my cost,” said Bhavi Mehta, a partner at Bain & Co. and its global lead for advanced analytics in financial services. “As AI moves toward more sophisticated reasoning and agentic workflows, the tokens required for a given task can vary significantly. That makes understanding cost alongside business value increasingly important as banks scale AI,” he added.
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