Data Centres

xAI co-founder departures deepen as another exit looms

13 March 2026
2 minutes
The leadership shake-up at Elon Musk’s AI venture xAI appears to be accelerating, with another co-founder departing the company and reports suggesting a further exit could soon follow.
xai elon.png
xai elon.png

Co-founder Zihang Dai has left xAI, according to multiple reports this week, marking the latest in a string of high-profile departures from the AI start-up founded by Elon Musk in 2023.

Sources cited in US media reports also say that another co-founder, Guodong Zhang, has told colleagues he intends to leave the company, although his departure has not yet been formally confirmed.

The exits add to a growing list of founding team members who have stepped away from the company in recent months, raising questions about stability within the organisation as it continues to develop its AI models and expand infrastructure to support them.

xAI was established by Musk as a rival to leading artificial intelligence developers, including OpenAI, Google and Anthropic. The company is best known for developing the Grok family of large language models, which are integrated with Musk’s social platform X Corp.

However, the start-up has experienced a wave of leadership changes since the start of 2026. Several other founding figures, including researchers who helped build the company’s early model architecture, have reportedly moved on to new roles across the AI ecosystem.

The potential departure of Zhang could prove particularly notable. He has led a number of internal engineering initiatives at xAI, including projects linked to coding and developer-focused tools built around the Grok model family.

While departures from early-stage companies are not unusual, the pace of change at xAI highlights the intense competition for experienced AI researchers and engineers as the global race to build and scale large language models accelerates.

The broader industry is currently investing billions of dollars in computing infrastructure, specialised chips and data centre capacity to support AI training and inference workloads – creating significant demand across the digital infrastructure sector.

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