Sam Altman got fired from OpenAI on November 17th. Five days later, he was back as CEO. Most of the board that fired him was gone. The whole thing happened so fast it revealed something important about how we should think about depending on OpenAI at enterprise scale.
What actually happened
The OpenAI board fired Altman citing a lack of candour. Within 24 hours, almost all of OpenAI's staff signed a letter threatening to resign if Altman was not reinstated. Microsoft, which had invested $13 billion, stated it would hire Altman and the departing team. The board capitulated. A new board was formed. Altman returned as CEO. The entire event compressed a governance crisis that typically unfolds over months into five days.
The structure that produced the crisis
OpenAI operates as a non-profit that controls a capped-profit entity. The board of the non-profit has fiduciary duty to the mission of beneficial AI, not to investors or revenue. This structure is why Microsoft's $13 billion investment did not give them board control. The structure also means the board can theoretically act against commercial interests if they believe safety requires it. That tension, commercial pressure vs safety-focused governance, is structural, not resolved by Altman's return.
What it means for enterprise OpenAI dependency
Enterprises with significant revenue or operational dependency on OpenAI APIs now have a data point: OpenAI can experience governance instability significant enough to threaten the company's continuity within a five-day window. The appropriate response is not necessarily to abandon OpenAI APIs, but to have a model diversity strategy: applications that can route to alternative models if needed, evaluated regularly, not just planned.
The Microsoft consolidation
Microsoft came out of the OpenAI crisis with more effective influence, not less. Altman is back as CEO with backing from Microsoft. The new board has investor representation. Azure OpenAI Service, which routes enterprise OpenAI usage through Microsoft's infrastructure, becomes more attractive as the compliance and continuity layer between enterprises and OpenAI's governance uncertainty.