McKinsey: AI Can Cut Banking Cost Base by Up to 20%, But Most Banks Are Stuck Boosting Individual Productivity
McKinsey: AI Can Cut Banking Cost Base by Up to 20%, But Most Banks Are Stuck Boosting Individual Productivity #
Artificial intelligence could reduce the global banking industry’s total cost base by 15 to 20 percent, but most institutions remain focused on productivity enhancements that have yet to move the financial needle, according to McKinsey & Company’s Global Banking Annual Review 2025, published in late October.
McKinsey calculates that gross cost reductions in some categories could reach as high as 70 percent, translating into a 15-to-20 percent net reduction across total operating expenses. The consultancy describes AI as a tool that offers significant efficiency gains for banks, but also as a force that could erode traditional profit pools.
The firm points to a paradox in current AI deployments. While nearly 80 percent of companies report using generative AI in at least one business function, a similar proportion report no meaningful impact on their bottom line. Banks have largely confined the technology to individual productivity rather than transforming end-to-end processes or business models, the report said.
McKinsey identifies agentic AI, which it defines as autonomous systems capable of reasoning and acting with minimal human oversight, as the area it expects to generate the most value next. Early use cases have already cut manual workloads by 30 to 50 percent, and the firm envisions a model in which a single employee supervises between 20 and 30 AI agents managing complex workflows end to end. Used as a co-pilot alongside a human banker, generative AI might lift individual productivity by a factor of roughly 1.2; in a fully supervised agentic setup, that multiplier could reach 20 times.
McKinsey warned that the window for first-mover advantage is narrowing. Early adopters that embed agentic AI into their operating models could see returns on tangible equity rise by as much as four percentage points relative to slower-moving rivals.
The efficiency gains carry a disruption risk. As consumers increasingly use AI agents to compare deposit rates, optimise credit terms and shift balances automatically, the customer inertia that has historically anchored banking relationships will erode. McKinsey estimates that if banks fail to reposition their business models in response, global banking profit pools, currently running at around $1.2 trillion annually, could shrink by as much as $170 billion, or roughly 9 percent, over the next decade, pushing average returns on tangible equity below the cost of capital for many institutions.
The report argues that even smaller banks can capture disproportionate rewards by deploying capital and technology with focused precision rather than broad strategies, since agentic AI reduces some of the scale advantages that larger institutions have historically held, the firm said.
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