Elon Musk on Thursday challenged OpenAI’s legal team during his third day on the stand, sharpening a high-stakes courtroom fight over the company’s shift from a nonprofit to a for-profit venture. The dispute centers on why and how the AI developer changed course, what that means for its mission, and who holds power over systems that influence millions of users.
Elon Musk on Thursday sparred with an attorney for OpenAI during his third day of testimony in the contentious trial over the company’s pivot from nonprofit status to a for-profit venture valued at hundreds of billions of dollars
The proceedings spotlight the tension between funding the rapid growth of artificial intelligence and keeping promises about public benefit and safety. At stake is the model for governing AI firms that need massive capital while claiming to act in the public interest.
What Sparked the Court Fight
The dispute traces to OpenAI’s transition in 2019 from a pure nonprofit to a “capped-profit” structure, designed to attract investment while limiting investor returns. Musk, an early backer and co-founder, has been a vocal critic of that move. His testimony this week placed the company’s mission and governance under fresh scrutiny.
OpenAI has argued that scaling large models demands huge spending on computing power, research talent, and infrastructure. Those costs surged as its products gained mainstream use. The company’s rapid growth drew new capital and attention, along with questions about who benefits from the technology and on what terms.
How OpenAI Changed Its Structure
OpenAI created a limited partnership that allows outside investment with a return cap, while a nonprofit board maintains control. Leaders have said the setup balances two goals: raising funds needed to compete and keeping a focus on safety and broad benefit. Supporters view the model as a practical way to finance long-term research.
Critics see a shift away from the original public-interest mission. They argue that a for-profit arm can tilt priorities toward growth, partnerships, and product speed. Tension over this balance has grown as the organization’s valuation soared in private transactions, with some estimates placing it above $100 billion.
Competing Narratives in the Courtroom
Thursday’s exchange highlighted two narratives. Musk’s side questioned whether the restructured entity diluted the original mission and public oversight. OpenAI’s legal team focused on the need for capital and the safeguards embedded in the capped-return design and board governance.
- Musk’s critique: mission drift and public benefit risks.
- OpenAI’s defense: funding requirements, capped returns, and board controls.
The testimony underscored a broader industry debate: can companies both build powerful systems at scale and stay anchored to public interest commitments without slipping into profit-first decision-making?
The Stakes for AI Governance and Safety
AI development requires extensive compute and specialized staff. Industry estimates place training costs for leading models in the tens to hundreds of millions of dollars. That financial reality pressures labs to find deep-pocketed backers and commercial pathways.
Safety advocates worry that market pressures can shorten testing cycles and reduce transparency. Company leaders counter that revenue funds red teams, model evaluations, and alignment research. The right balance remains unsettled, and the court battle has turned that policy question into a legal one.
What to Watch Next
The outcome could influence how AI labs structure themselves and whom they answer to. It may also steer investor expectations about returns, control, and disclosure. If courts affirm the current model, the capped-profit template could spread. If the court finds problems with the shift, other AI firms may rethink governance plans.
Regulators in the United States and abroad are also shaping the environment with new rules on safety, transparency, and competition. Any ruling will land in a policy space that is tightening as AI tools spread across schools, offices, and government agencies.
Thursday’s clash showed how questions about mission, money, and control are no longer academic. They are being tested under oath. As testimony continues, the central issue remains clear: can an AI lab scale at speed, take in large sums, and still keep the public interest front and center?
