BENGALURU: As enterprises race to deploy GenAI, a new challenge is emerging for IT firms: token maxxing. Tokens-the units consumed whenever large language models process information-have become the fundamental currency of AI. But after an initial wave of experimentation, IT services companies are increasingly warning that relentless token consumption without measurable business outcomes could become the industry’s next cost problem.Token maxxing treats AI consumption as a measure of productivity, pushing employees and enterprises to use increasing amounts of compute and tokens. The term gained currency in Silicon Valley, where the double “xx” in “maxxing”-borrowed from internet and gaming slang-denotes aggressive optimisation. As enterprises move from pilots to large-scale deployments, IT firms are increasingly focused on linking token usage to business value rather than raw consumption. Arumugam Kumaradassan, vice-president and head of AI industrialisation and enterprise IT automation at Cognizant, said, “Tokens are an input to delivery, not a measure of value, and token consumption is simply a cost signal, tracked for discipline, licence governance and capacity planning. When token consumption is treated as the primary metric, costs scale linearly with demand without a corresponding return in business outcomes.”
Kumaradassan said the company has implemented metering and value-linkage capabilities that connect token consumption to business workflows and outcomes. “As the industry moves towards outcome-based models, token spending will reveal the cost of achieving those outcomes,” he said.At Happiest Minds, executive vice-chairman Joseph Anantharaju said the company is developing capabilities for token metering and optimisation as enterprises scale agentic AI deployments. “I think that’s going to be very important-the ability to meter it,” he said.The company is also evaluating outcome-based commercial models that combine software, agents, platforms and AI consumption.“The outcomes that customers want can be delivered through a model that combines the solution, token consumption and the number of agents deployed,” Anantharaju said.The debate is becoming increasingly relevant as AI projects move from pilots to production. “One of the most important currencies in an agentic AI transformation are tokens. We are now looking at our token consumption,” said Salesforce chief digital officer Vala Afshar. “We’re also looking very closely at how much of these tokens actually automate tasks by agents, because it’s wasteful to just spend tokens unless you’re creating value at the speed of need.” Yet technology providers are becoming wary of turning token consumption into a pricing model.Mphasis CEO Nitin Rakesh said customers increasingly bear variable token costs as usage expands. “What we are pricing is the economic outcome. There is a base price that you (client) will pay me, and the rest will be linked to the outcome I can drive,” he said.
