Sam Altman’s Counter-Rebellion Leaves OpenAI Leadership Hanging in the Balance

SAN FRANCISCO—Two days after Sam Altman was ousted from OpenAI, he was back at the company’s office, trying to negotiate his return.

The former chief executive officer entered with a guest badge on Sunday and posted on X: “first and last time i ever wear one of these.”

The leadership of the company that created the hit AI chatbot ChatGPT remained unclear Sunday, as investors and many employees pushed over the weekend to restore Altman. He has been engineering a countercoup to retake control of one of Silicon Valley’s most valuable and high-profile startups.

The abrupt shake-up at OpenAI turns on one of the oldest tales in Silicon Valley: a breakup between a founder and his board.

But in this case it was a very particular kind of founder—the face of Silicon Valley’s artificial-intelligence revolution—and a very particular kind of board, which was tasked with making social good a priority over profit. The rupture threatens the future of the company and the billions of dollars investors had put into it.

Altman has also been considering starting his own venture, potentially with talent from OpenAI. He is pursuing both tracks: On Sunday morning, Chief Technology Officer and interim CEO Mira Murati sent a note to staff saying Altman would be returning to the San Francisco office later that day as discussions to reinstate him continued.

Over the weekend, Altman made clear to his allies that if he does return, he wants a new board and governance structure, people familiar with the matter said.

Two days after the board fired Altman, different explanations persisted for the initial firing. The board said Friday it pushed out the CEO after it concluded he hadn’t been candid with the company’s directors. It didn’t elaborate.

Over the weekend, people close to Altman said the ouster had more to do with disputes around the safety of the company’s artificial-intelligence efforts and a power struggle with one co-founder and board member in particular, Ilya Sutskever.

On Sunday, a person familiar with the board stood by the board’s statement citing Altman’s lack of candor. This person said there was no single precipitating incident but rather a mounting loss of trust over communications with Altman that led it to remove him as CEO. The person declined to offer examples.

The ouster from OpenAI wasn’t the first time Altman was asked to leave a company. Several years ago, senior leaders at the venture firm Y Combinator asked Altman to step down as president after mounting concerns about the time he was spending on his other business endeavours, including at OpenAI, according to investors briefed by the venture firm’s executives—information not previously reported.

In addition to OpenAI, Altman recently hatched plans for two new business endeavours. He enlisted Apple’s former chief design officer, Jony Ive, to create a consumer hardware device. And he recently spent weeks in the Middle East gauging investor interest for a new startup aiming to create low-cost chips needed to train OpenAI’s artificial-intelligence models, people familiar with the matter said.

It is unclear whether those efforts, or the communication around it, played into Altman’s dismissal. Bloomberg earlier reported on the new chips venture. The Information and the Financial Times earlier reported the new Ive venture.

With his firing from OpenAI, Altman quickly got the upper hand in terms of public messaging. The board didn’t use a communications or law firm in its dealings, people familiar with the board said, expecting that the OpenAI team would help them. But Altman had loyalty from investors and employees.

The board ended up isolated as social media exploded with shock and support for Altman. His largest backers, including Microsoft and Thrive Capital, immediately on Friday began pressing for Altman’s position to be restored. Microsoft CEO Satya Nadella began working with Altman that evening on his next steps, people familiar with Altman said.

Despite his business success, Altman had been losing the support of a board whose constituents changed as the company’s commercial efforts powered ahead. It was a board structure that he had ironically helped create and publicly promoted as he encountered questions about AI safety.

Before Friday’s dust-up, the board consisted of six people, including Altman. Then, it abruptly removed Greg Brockman, OpenAI’s president and a close friend of Altman’s, and voted to oust Altman. None of the four board members remaining were affiliated with the company’s big investors. It isn’t clear whether the vote was unanimous.

The board that took the action was down from the nine seats it had earlier in the year and lacked at least one key prior Altman backer. Earlier this year, Reid Hoffman, a Silicon Valley venture capitalist with a long history of supporting Altman, stepped down after starting a rival company to OpenAI.

Separately, Shivon Zilis, a tech executive at Elon Musk’s brain-implant startup Neuralink, and Will Hurd, who started a presidential campaign, also left this year.

The board had been working to fill those empty seats for months, though the process stalled, according to a person familiar with the matter.

The other four directors are: Adam D’Angelo, a former Facebook executive and the founder of the question-and-answer website Quora; Tasha McCauley, an adjunct senior management scientist at Rand; Helen Toner, a director at a Washington nonprofit; and OpenAI’s chief scientist, Sutskever.

Altman this weekend was furious with himself for not having ensured the board stayed loyal to him and regretted not spending more time managing its various factions, people familiar with his thinking said.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion