The Hidden Dollar Drain Behind India’s AI Rush

by · Inc42

SUMMARY

  • For SaaS and enterprise firms, a growing share of their technology spending is flowing overseas through AI inference bills
  • While India emerges as one of the world’s largest consumers of AI, much of the underlying economic value accrues abroad.
  • Analysts believe AI infrastructure dependence could emerge as a similar long-term concern for India’s digital economy, especially if the country scales AI adoption without building enough domestic capabilities.
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India’s AI boom may be quietly creating its next major dollar outflow problem.

As startups and enterprises rush to embed generative AI and large language models into everything from customer support to internal workflows, a growing share of their technology spending is flowing overseas through AI inference bills.

AI inference refers to the process of using trained AI models to generate responses and execute tasks in real-world applications. Unlike traditional software, AI-native applications incur a fresh compute cost every time a user interacts with them through a chatbot query, as well as each instance of personalisation in recommendation engines or workflow automation powered by AI models. These costs are typically measured in tokens, the basic units of data processed by AI models.

While India emerges as one of the world’s largest consumers of AI, much of the underlying economic value accrues abroad. 

SaaS giant Zoho’s cofounder Sridhar Vembu recently likened the phenomenon to an ‘oil import bill’ for the AI era, warning that dependence on foreign AI compute infrastructure could become a vulnerability for countries like India. Zoho itself spends ‘a few million a year’ on AI model subscriptions, disclosed Vembu.

Inc42 dug deeper into the problem. At what stage of a startup’s lifecycle does AI inference costs become a material factor? How can startups mitigate these cost concerns? And should India have a plan to retain some of the revenue value in such AI inference calls? 

Earning In Rupees, Spending In Dollars

At Gurugram-based beautytech startup Style Lounge, AI inference and model usage already account for nearly 8–12% of the company’s AI and cloud infrastructure costs, which it expects could rise to as much as 25% as more customer journeys become AI-led. 

The company, founded in 2024, relies on AWS for cloud and GPU infrastructure, alongside OpenAI APIs, image analysis models, and other AI tooling layers. Most serious AI workloads today are ultimately billed in dollars or tied to dollar-linked pricing, meaning that even if revenues are earned in rupees, the underlying cost base remains global.