There is a paradox that is happening in AI right now. Demand for AI productivity tools such as Claude Code is higher than ever as companies drive adoption. But it is driving AI costs higher than that of human capital.
There have been multiple instances of employees exhausting a year’s worth of AI budget within months.
According to technology news publication The Information, Uber chief technology officer Praveen Neppalli Naga recently stated in an internal memo that the company burnt its 2026 AI budget in four months.
This cost is likely to increase as large AI enterprises such as Anthropic and GitHub move from the current flat subscription structure to usage-based pricing. This is resulting in some companies hiring people instead, building guardrails to keep AI costs in check and optimising their AI usage.
Rising AI usage
Unlike the software-as-a-services era, where the software was meant for humans, seat-based subscription does not make sense with AI agents becoming mainstream in enterprises, said startup founders ET spoke with.
AI agents process instructions and generate responses by consuming tokens, and more tokens means more computing cost for the AI companies. To manage the cost, they are moving towards usage or outcome-based pricing.
GitHub in a blogpost said that starting June 1, the company will transition to usage-based billing as absorbing the escalating inference, or computing, cost is no longer sustainable.
Anthropic has changed the billing framework for its Claude model for enterprise customers and has started billing based on usage rather than a fixed fee, The Information reported in April. The founder of a US-based AI services startup confirmed this to ET. Emails sent to Anthropic did not elicit any response till press time.
This means increased AI cost for startups and enterprises.
For Latentforce, an AI modernisation platform, spending on tokens has skyrocketed in the last six months, though Claude’s usage-based model is yet to take effect for the company, said cofounder Aravind Jayendran.
“Six months ago, our token cost was `20,000 per month, but now it is already moving to `2-3 lakh per month,” he said.
While the return on investment justifies the cost, he said the same cannot be said for several enterprises that Latentforce is helping adopt AI.
Jayendran said his clients in the knowledge services sector are hiring people rather than deploying AI as the former is cheaper currently. This includes jobs such as data entry and documentation processing.
Another founder, who optimises usage of large language models for enterprises, told ET on the condition of anonymity that many Indian enterprises still rely more on human capital than AI given the high costs of running and maintaining the systems.
In a post on Reddit, a founder said with AI getting expensive, his company cancelled five of its AI subscriptions and hired two mid-level developers instead.
Optimise, tweak
Companies for which AI tools are a mainstay, meanwhile, are optimising internal AI usage and tweaking their revenue models.
Latentforce is exploring optimising its AI model usage by a mixture of open source and frontier models.
The founder of a Bengaluru-based unicorn said his company has put agentic guardrails in place to ensure that tokens are used for the approved projects and flag if the usage hits upper limits. “This is to ensure that they are used right, when we are spending so much,” he added.
Vijay Rayapati, cofounder of Atomicwork that helps clients automate employee requests and IT service workflows, told ET that his company offers hybrid pricing—a flat rate with limits on tokens and an option for additional usage with extra payment.
“Enterprises need visibility on budget and fixed cost helps with that. However, they will need to pay for their consumption as the AI companies have also increased the cost of APIs for new models,” he said.
Vivek Khandelwal, cofounder of agentic AI application CogniSwitch, said in the last few months, the company has also shifted towards API pricing and token usage.
