OpenAI Targets Specialized Industries as Enterprise AI Demand Grows

OpenAI is expanding its focus on specialized industries such as chip design, life sciences and financial services while lowering AI model prices to compete with cheaper open-source alternatives, Chief Financial Officer Sarah Friar said Monday.

Speaking at Goldman Sachs’ Communacopia + Technology Conference in San Francisco, Friar said enterprise customers increasingly want artificial intelligence systems designed for specific business tasks rather than broad, general-purpose applications.

OpenAI is also experimenting with outcome-based pricing, which would tie costs more closely to the results customers receive instead of charging primarily according to usage. The shift comes as companies demand clearer returns from growing investments in generative AI.

Competition has intensified as OpenAI faces rivals including Anthropic and lower-cost Chinese open-weight AI models. Friar said OpenAI is responding by improving affordability while demonstrating how its technology can accelerate complex industry workflows.

She pointed to OpenAI’s development of its “Jalapeno” chip as an example. According to Friar, the company used its own AI models to complete the chip design and reach tape-out, the stage when a finished design is sent for manufacturing, within nine months.

OpenAI has also sharply reduced the price of its budget-focused Luna model. Friar said Luna pricing was cut by 80%, contributing to an approximately tenfold increase in usage. She argued that running Luna can cost less than deploying some Chinese open-source models through cloud infrastructure, citing Z.ai’s GLM 5.3 as an example.

Meanwhile, OpenAI’s Codex coding assistant has grown to 25 million users, highlighting rising adoption of specialized AI tools.

Enterprise business is becoming an increasingly important growth engine for OpenAI. Friar said enterprise revenue jumped 32% between June and July, compared with 20% growth in the company’s overall annualized revenue during the same period.

By mid-year, enterprise and consumer revenue were roughly evenly divided. That puts OpenAI ahead of its previous goal of achieving revenue parity between the two segments by the end of the year as corporate AI adoption continues to accelerate.