OpenAI’s pursuit of billions in revenue amid staggering losses raises questions about AI economic sustainability

OpenAI projects up to $14 billion in losses by 2026 despite aiming for $100 billion annual revenue by 2029, as the industry grapples with unsustainable costs and subsidised growth strategies.

The cheapness of modern AI subscriptions can make the economics look almost magical. A heavy Claude Code user can generate billions of tokens a year, and at standard API rates that usage would cost far more than a flat monthly plan. The gap is so wide that the user experience can feel heavily subsidised, with investors effectively absorbing much of the bill while the market decides whether these services will become indispensable.

That tension is exactly why OpenAI’s finances have attracted such intense scrutiny. According to reporting based on internal documents reviewed by The Information, the company could lose about $14 billion in 2026, with losses remaining substantial before any expected turn to profit later in the decade. The same reporting says OpenAI is aiming for roughly $100 billion in annual revenue by 2029, but only after years of steep spending on model training, infrastructure and staff.

The scale of that spending helps explain the race to sign up users now, even at prices that appear far below the true cost of serving them. OpenAI’s ChatGPT Plus plan is priced at $20 a month, while the company’s own pricing page shows that API usage is billed separately and that different tiers carry different limits and features. That split between consumer subscriptions and metered developer use has become central to the company’s business model, as it tries to balance growth, access and the enormous cost of running large language models.

For critics, the broader concern is not just whether the pricing is temporary, but whether the present model can support the industry’s ambitions. The Information’s reporting suggests that a large share of OpenAI’s spending goes straight back into training and operating its models, with projected losses stretching into the second half of the decade. Supporters argue that this is the normal cost of building a new platform category; sceptics see a subsidy-fuelled land grab whose real economics have yet to be proved.

Disclaimer: This article is intended to inform and educate, not to recommend or endorse any financial product, investment or strategy. Please consider your own financial circumstances and seek professional advice where appropriate before making financial decisions.