Banks move to rein in soaring AI agent costs, McKinsey says

Banks worldwide are trying to curb the soaring cost of AI agents, as spending on the tokens that power them could easily reach 20% of total labor costs, according to McKinsey's Global Banking Annual Review, Reuters reported on November 10.

Enter "AI FinOps"

Responsibility for controlling AI-related spending has shifted to new teams that some banks call AI FinOps. Initially, banks sought to rein in costs with systems that routed employees to different AI models based on the complexity of their queries.

"But those models are ineffective when AI agents are working, because they communicate with each other and tokens quickly add up," said Vik Sohoni, a senior partner at McKinsey and one of the report's authors, in an interview with Reuters.

As a result, banks are becoming more selective about where they deploy agentic AI, focusing on areas with the strongest expected returns. Productivity savings are relatively easy to measure, but banks are increasingly looking at AI-driven revenue growth to decide where higher spending is justified, Sohoni said.

Customers are adopting fast

Customers are adopting AI much faster than previous technologies, according to the report. McKinsey expects AI agents to become widely used within three years, compared with the five to 10 years it took mobile internet to gain broad adoption.

A McKinsey survey of 46,000 retail banking customers worldwide found that most already use AI to compare banking services, find higher-yield savings accounts and refinance or consolidate debt. Among AI users, 72% said they would allow a banking agent to carry out one financial task, although they would cap autonomous approvals at $500. Meta's Muse agent was downloaded 5 million times in the US in its first 22 days after launch.

Pressure on profits

While AI agents could help banks boost revenue and cut costs, they could also pressure profits by shifting deposits from non-interest-bearing accounts into higher-yielding ones. So far the impact has been limited because most banks block external AI agents from authorizing transactions within their systems.

Sources: Investing.com / Reuters, McKinsey Global Banking Annual Review 2026