Report says former Nvidia chief doubted the executive now serving as interim CEO

Jensen Huang, who resigned as Nvidia's chief executive this week, privately questioned the abilities of the finance chief who has now taken over from him on an interim basis, TechCrunch reported, citing a Wall Street Journal account based on an anonymous source.

According to that account, Huang described chief financial officer Collette Kress as "a deer in the headlights" during a presentation in the summer. He was also reported to have said she could not help him guide the company's strategy or decision-making. Neither Huang nor Kress is quoted as confirming the remarks in the report.

A dispute over financing chip sales

The comment was reportedly made at a meeting with Nvidia's finance team about plans to offer guarantees worth billions of dollars to data center operators that could not pay for the company's chips upfront. The report says Kress had raised questions about these credit-based arrangements. She wanted clearer ways to judge which deals were worthwhile, how to value the guarantees, and how to measure returns.

Earlier in the year, Kress reportedly reduced Nvidia's commitment to a large OpenAI data center project in Ohio. Nvidia had discussed providing up to $250 billion in credit to OpenAI but ultimately committed $105 billion.

Kress has worked at Nvidia for more than 13 years. Before that, she was a senior vice president and CFO in a finance unit at Cisco.

Leadership in transition

Huang stepped down on Thursday after more than 33 years in the top job, following reports about his personal conduct. Nvidia is also investigating a possible Chinese espionage plot, according to the report. The company is now looking for a permanent chief executive.

For people who follow the computer and internet industry, the episode shows how closely AI hardware sales have become tied to financing. Some data center builders depend on credit from chipmakers to buy equipment. The way Nvidia's next leaders handle those deals could affect how quickly new computing capacity is built. It could also shape how much financial risk chip suppliers take on as AI infrastructure expands.