According to a Tuesday (April 21) Wall Street Journal (WSJ) report, this effort is part of the artificial intelligence (AI) startup’s effort to shift away from “side projects” and focus on coding and enterprise customers.
Codex now has more than 4 million weekly active users, OpenAI has said, compared to 3 million two weeks ago and more than 2 million last month.
This comes as the company is engaged in fierce competition with fellow startup Anthropic for enterprise clients. Anthropic, the WSJ added, has become the top AI provider for businesses partially because of the viral success of its coding and AI agent offerings.
In an interview with the WSJ, OpenAI Chief Revenue Officer Denise Dresser said its Codex consulting partners will help the company reach more potential enterprise customers than it could on its own.
“Helping companies bridge that gap between how to use it, how to expand it and how to move even more quickly is part of our responsibility, and these partnerships are going to allow us to help scale that to the world,” said Dresser, who was appointed last year.
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Beyond using Codex to help customers with things like updating code, OpenAI’s consulting partners will help introduce Codex “into every single line of business,” she added. That includes areas such as marketing, finance and sales, where coding agents and tools aren’t as common.
Dresser told the WSJ that Codex and Frontier — a platform debuted in February to help businesses develop AI agents — are designed to help automate parts of all knowledge work.
In related news, PYMNTS wrote last week about the challenge facing companies who want to capitalize on new AI tools while still controlling costs. The report followed comments from Uber tech chief Praveen Neppalli Naga, who saw the company’s budget balloon while using Anthropic’s coding tool Claude Code.
“AI coding tools don’t behave like traditional software,” that report said. “The cost isn’t fixed. It rises with use. Each interaction consumes compute, measured in tokens, and the cost of those tokens add up quickly. At Uber’s scale, usage didn’t grow steadily. It surged. And costs followed faster than anyone expected.”
The report goes on to note that AI tools that had once been added to engineering workflows as productivity aids are now “line items with variable, consumption-driven costs.” Companies that adopted them at scale without modeling usage are faced with invoices that don’t match budgets.
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