Sam Altman recently disclosed that OpenAI’s annual revenues already exceed the previously-reported US $13 billion figure, and he believes the company is on track to hit around US $100 billion in annual revenue by 2027.
This projection underscores OpenAI’s confidence that the current surge in artificial-intelligence deployment isn’t just incremental but transformative. Altman noted that the company’s growth is being driven not only by consumer products like ChatGPT but also by enterprise deals, enterprise AI infrastructure, and a broader ecosystem of AI tools — all contributing to the revenue base. The leap from tens of billions to one-hundred billions reflects ambitious expansion, aggressive scaling and deep investments in AI infrastructure, compute, and model development.
However, the numbers also raise strategic questions. With revenue growth projected to accelerate so rapidly, OpenAI is under pressure to maintain infrastructure build-out, manage costs of compute and data-centre operations, and defend its lead amid growing competition. Achieving a ~$100 B revenue target by 2027 would imply very large scale in enterprise adoption, global reach, and monetisation of new AI products and services — all while navigating regulatory, safety and business-model risks.
For the broader industry and economies such as India’s, this signals both a massive opportunity and a caution. On one hand, the AI-market size is rapidly expanding, meaning local companies, startups and policymakers may benefit from expanded demand for AI infrastructure, services and applications. On the other hand, meeting these huge revenue goals requires underlying capabilities — in compute, skills, governance and deployment — that may not exist yet everywhere. The benchmark set by OpenAI suggests that to compete or partner in this wave, stakeholders must build capacity and strategy now.
