OpenAI is expanding its artificial intelligence technology into specialised industries including semiconductor design, life sciences and financial services, as the company looks to grow enterprise adoption while reducing the cost of using its models.
Speaking at Goldman Sachs' Communacopia + Technology Conference in San Francisco, OpenAI Chief Financial Officer Sarah Friar said businesses are increasingly seeking AI systems designed around specific industry tasks. The company is also experimenting with pricing models linked to business outcomes rather than solely charging based on usage.
Chip design is one area where OpenAI has already applied its own technology. The company used its AI models during the development and optimisation of Jalapeño, its custom inference chip co-developed with Broadcom.
OpenAI and Broadcom unveiled Jalapeño in June. The chip moved from initial design to manufacturing tape-out in nine months, with OpenAI saying its models were used to accelerate parts of the design and optimisation process. Tape-out refers to the stage at which a chip's design is finalised and prepared for manufacturing.
The company is positioning such applications as an example of how AI could help engineers shorten development cycles and improve computing efficiency. OpenAI has said that better chip performance could eventually contribute to lower costs for running AI models.
Alongside specialised enterprise applications, OpenAI is using pricing as another lever to increase adoption. Friar said the company recently reduced the price of its lower-cost Luna model by 80%, which was followed by an approximately tenfold increase in usage.
She also said deploying Luna could be cheaper than running some Chinese open-weight models through cloud infrastructure, citing Z.ai's GLM 5.3 as an example. The comparison reflects growing competition between proprietary AI providers and open-weight models, which have often been positioned as lower-cost alternatives for businesses.
OpenAI's enterprise business is also expanding. According to Friar, enterprise revenue increased 32% between June and July, compared with 20% growth in the company's overall annualised revenue during the same period. Its enterprise and consumer businesses had reached roughly an even split by the middle of 2026.
The company is now looking to combine lower model prices with industry-specific AI applications as businesses increasingly evaluate artificial intelligence based on measurable productivity gains and return on investment.
For OpenAI, the strategy broadens its focus beyond consumer-facing products such as ChatGPT, extending its models deeper into specialised enterprise workflows and the infrastructure used to power AI itself.
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