Bank of America analysts examined OpenAI’s updated long-range projections and found the company is targeting $283 billion in revenue by 2030, accompanied by approximately $665 billion in cumulative compute spending through 2030. The bank said these figures point to a materially larger demand backdrop for artificial intelligence that has implications for large internet firms and cloud service providers.
In the bank’s read of OpenAI’s fundraising materials, the expanded revenue and spending outlook reinforces an enlarged AI-driven revenue pool across advertising, commerce and productivity applications. The projections imply materially higher demand for both AI services that monetize directly and the underlying compute infrastructure that supports them.
At the same time, the analysis flagged near-term profitability pressures. Reports cited by the bank indicate inference costs rose sharply - described as having “quadrupled” in 2025 - which in turn accelerated additional compute purchases and helped push OpenAI’s gross margin down to 33% in 2025 from 40% in 2024. Those margin dynamics underline the trade-off between rapid growth in usage and the cost of supporting large-scale model inference.
The bank also pointed to OpenAI’s consumer-facing business as a potential major entrant in the advertising market by the end of the decade. Using the company’s own breakdown, the analyst estimated ad revenue potential in the range of $45 billion to $75 billion by 2030. If realized, that figure could translate into roughly a 1-2% annual sector revenue headwind for incumbents such as Google, Meta and Amazon.
On infrastructure, the bank noted a strategic shift back toward a partner-led model for large-scale compute deployments. That pivot creates incremental opportunities for hyperscalers to supply capacity. The analyst highlighted that established cloud providers can leverage existing cash flows and proprietary chips to compete for significant AI infrastructure contracts.
Overall, Bank of America said the updated OpenAI projections strengthen its positive view of long-term demand across internet and cloud ecosystems, while calling attention to margin pressures and competitive effects in advertising and infrastructure markets.
Key points
- OpenAI is targeting $283 billion in revenue by 2030 and about $665 billion in cumulative compute spending through 2030, expanding demand prospects for AI-related services.
- Rising inference costs and a drop in gross margin to 33% in 2025 from 40% in 2024 highlight profitability pressures tied to compute intensity.
- OpenAI’s consumer business could generate $45 billion to $75 billion in ad revenue by 2030, posing a 1-2% annual sector revenue headwind for major ad platforms; hyperscalers may gain infrastructure contracts as OpenAI shifts to a partner-led build-out.
Risks and uncertainties
- Profitability risk - steeply higher inference costs in 2025 reduced gross margins, indicating continued cost pressure for AI service providers and their infrastructure partners.
- Advertising market impact - a sizeable consumer ad business from OpenAI could create revenue displacement risks for incumbent ad platforms.
- Infrastructure competition - while hyperscalers have opportunity to supply capacity, competition for large AI contracts could alter margins and capital deployment for cloud providers.