Ex-OpenAI Research Chief Aims to Bring AI to Manufacturing

OpenAI’s former chief research officer is reportedly raising $70 million for a manufacturing-focused artificial intelligence (AI) startup.

Arda, co-founded by Bob McGrew, is raising money at a valuation of $700 million, the Wall Street Journal (WSJ) reported Wednesday (March 4), citing sources familiar with the matter.

As the report noted, Arda—like many other startups—takes its name from “Lord of the Rings” author J.R.R. Tolkien. In this case, Arda means “world,” and is—per the WSJ—a reference to the company’s aim of connecting the AI and physical worlds.

Sources told the WSJ that Arda is developing an AI and software platform, including a video model that analyzes footage from factories and then uses it to train robots to run plants autonomously.

Arda’s software will coordinate machines and humans across the production process, from product design and manufacturability to finished goods, the report added. The WSJ says McGrew’s role at OpenAI involved training robots to perform tasks in the physical world.

He is among a group of former OpenAI executives who have gone on to start AI companies of their own in recent years.

Mira Murati, the company’s one-time chief technology officer, launched Thinking Machines last year. Ilya Sutskever, an OpenAI co-founder, helped launch a company called Safe Superintelligence in 2024.

In related news, PYMNTS wrote last month about MIT research showing that early AI deployments in manufacturing “tend to be additive rather than transformative.”

“Companies introduce predictive maintenance models, computer vision inspection tools or demand forecasting algorithms, but leave underlying processes intact,” the report said. “This creates friction between automated recommendations and human workflows, limiting measurable productivity improvements.”

Manufacturing environments are especially complicated, as production lines rely on tightly sequenced tasks, supplier coordination and legacy industrial control systems. Introducing AI without harmonizing these systems can make more work for employees.

The research suggested that productivity gains arise only when companies link AI with organizational redesign. That includes shifting decision authority closer to data sources, standardizing data architectures and committing to workforce retraining.

“Once firms work through the adjustment costs, they tend to experience stronger growth,” said University of Toronto professor Kristina McElheran, a digital fellow at the MIT Initiative on the Digital Economy and one of the lead authors of the study. “But that initial dip in the downward slope of the J-curve is very real.”