Australia's biggest bank warns AI costs will surge as tasks grow more complex
Commonwealth Bank of Australia CEO Matt Comyn said companies will face unpredictable cost increases as they deploy AI for more demanding work, signaling a shift in how finance leaders should budget for the technology.
Speaking at an Australian Financial Review conference in Sydney on Tuesday, Comyn predicted businesses will tighten spending controls on AI through 2026 as adoption accelerates and boards demand proof of returns on investment.
Token costs don't scale linearly
Unlike consumers who pay fixed fees, corporate users pay based on tokens-units of text processed. Early AI projects kept costs low because tasks were simple.
"As models have evolved, with more reasoning, the access to tools, the amount of context that you can put into it-your token costs do not scale on a linear basis," Comyn said.
This nonlinear scaling creates a budgeting challenge. Finance teams accustomed to predictable cost structures now face variable expenses that grow faster than expected as AI tackles more complex problems.
Energy and workforce pressures compound the issue
Rising AI costs join other operational constraints in corporate Australia: managing workforce disruption and meeting the heavy energy and water demands of data centers supporting AI infrastructure.
CBA, which writes a quarter of Australia's mortgages, has positioned itself as an early adopter. Last week it hosted an AI summit with OpenAI CEO Sam Altman and hired the country's first chief AI scientist at a bank.
Higher costs may filter out low-value work
Comyn identified one potential benefit to rising expenses: they could reduce the volume of what he called "work slop"-low-value outputs like routine PowerPoints and documents.
"The scarcity is not around analysis or the preparation of information or PowerPoints or Word docs," he said. "You can be exponentially increasing them if you want to."
As costs climb, organizations may become more selective about which tasks warrant AI deployment, potentially forcing teams to focus on higher-impact use cases.
For finance professionals, this signals a shift in how to evaluate AI investments. Cost scrutiny will intensify alongside pressure to demonstrate measurable business returns. Learn more about AI for Finance and AI for Executives & Strategy to understand how to build business cases for AI spending.
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