OpenAI Unveils Plans to Move Codex Beyond Coders

OpenAI Unveils Plans to Move Codex Beyond Coders

OpenAI is expanding the uses of its coding agent for fields beyond software engineering.

The company announced Tuesday (June 2) that it is rolling out new plugins for its Codex agent designed for jobs in public equity investment, banking and sales, with plans to add features related to legal, marketing strategy and corporate finance down the road.

In addition, the artificial intelligence firm says it is working on an “open ecosystem” that lets partners develop and deploy their own plugins directly within Codex and OpenAI’s ChatGPT bot.

“More than 5 million people now use Codex every week,” the company said. “Codex started as a tool for software development, but it’s increasingly useful for more kinds of work. Non-developers—including analysts, marketers, operators, designers, researchers, investors, and bankers—make up about 20% of overall Codex users⁠ and are growing more than 3x as fast as developers.”

Last month saw reports that OpenAI had generated nearly $6 billion in first-quarter revenue due in part to Codex, business sales and tests of advertising on ChatGPT.

“The numbers show how quickly OpenAI is turning AI usage into revenue,” PYMNTS wrote. “They also show how the business is shifting. ChatGPT remains the company’s consumer anchor, but Codex and enterprise AI are becoming more important growth engines.”

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This is happening as a growing share of U.S. hourly workers are encountering AI on the job before they feel prepared for it, as recent PYMNTS Intelligence research has shown.

That study, “The Resilience Deficit: Labor Workers in an Automated Economy,” looks at how automation is reshaping confidence, job security and financial resilience for Labor Economy workers, or hourly workers earning up to $25 an hour and generally less than $50,000 per year.

“While AI is spreading across workplaces of every type, low-income workers are receiving less training, reporting lower confidence and showing fewer financial buffers to absorb disruption,” PYMNTS wrote last month.

The research found that 37% of Labor Economy workers had seen their employers introduce new AI or automation tools within the prior 12 months. Close to 60% of these workers said that they had received no training on the new technology, compared to 42% who said they had gotten instruction on the tools.

“AI investment is accelerating across industries, and companies are increasingly framing automation as a productivity tool rather than an experimental technology,” PYMNTS wrote. The report added that the data “suggested the bigger divide may not be about who encounters AI first. It may center on who has the resources to adapt once workplace changes begin.”