Nvidia CEO resigns: Will OpenAI, Microsoft and Google rethink their AI strategies?

Jensen Huang’s resignation as Nvidia chief executive could have consequences far beyond the world’s biggest AI chipmaker. OpenAI, Google and Microsoft are among the technology giants whose artificial intelligence ambitions depend on access to powerful computing infrastructure, including Nvidia’s GPUs. Huang’s departure comes as these companies spend billions of dollars building data centres, developing AI models and competing for computing capacity. The biggest question is whether Nvidia can maintain the partnerships and investment strategy that helped make it central to the global AI industry.

Nvidia CFO Colette Kress has taken over as interim CEO while the board considers a permanent successor. Reuters reported that investors are concerned a leadership change could affect Nvidia’s willingness to finance and support the wider AI ecosystem.

OpenAI and Nvidia’s proposed $100 billion investment

OpenAI has one of the most significant relationships with Nvidia. In September 2025, the companies announced a strategic partnership to deploy at least 10 gigawatts of Nvidia-powered AI infrastructure for OpenAI.

Nvidia also announced plans to invest up to $100 billion in OpenAI progressively as computing capacity is deployed. The first gigawatt was targeted for the second half of 2026, using Nvidia’s Vera Rubin platform.

This is a proposed investment ceiling, not evidence that the full $100 billion has already been transferred. For OpenAI, the leadership change raises questions about how the partnership will be managed and whether Nvidia will maintain the same level of financial and infrastructure support.

Microsoft’s AI plans are closely connected

Microsoft is another major stakeholder in this ecosystem. Its long-running partnership with OpenAI gives it access to the startup’s AI technology, while Azure provides cloud infrastructure for OpenAI services. Microsoft's 2026 annual report disclosed $13 billion in total funding commitments related to its OpenAI investment, of which $11.9 billion had been funded by June 30, 2026.

Microsoft also works with Nvidia to support AI computing infrastructure. Any disruption to Nvidia’s ability to deliver chips, systems or technical support could therefore have wider implications for the AI supply chain.

Google has an alternative, but still needs Nvidia

Google has an important advantage: it develops its own Tensor Processing Units (TPUs), which power many of its AI workloads, including Gemini. However, Google is not abandoning Nvidia. In October 2026, Google Cloud announced further infrastructure developments based on Nvidia’s Vera Rubin platform. Its strategy combines in-house chips with Nvidia hardware. This gives Google more flexibility, but also shows how deeply Nvidia remains embedded in the AI infrastructure market.

Huang’s departure does not automatically mean chip shortages, cancelled investments or broken partnerships. Nvidia’s products, engineering teams and customer relationships remain in place. But his leadership was central to building the company’s close relationships with major AI developers and cloud providers. OpenAI, Microsoft and Google will now be watching whether Nvidia’s next leadership team maintains the same pace of investment, product development and collaboration. The stakes are significant: the next phase of the AI race will depend not only on better models, but also on who can secure the computing power needed to build and run them.