A report that OpenAI missed internal growth targets was enough to shake confidence up and down the AI supply chain this week, sending chip and cloud stocks lower and raising new questions about how fast the market is actually expanding.
Shares of Nvidia fell more than 3%, while AMD dropped even further before recovering slightly in premarket trading. Oracle and other companies tied to OpenAI’s infrastructure push also declined.
The reaction followed a The Wall Street Journal report that OpenAI missed internal targets for both user growth and revenue tied to ChatGPT. The company had been aiming to reach one billion weekly active users by the end of 2025, a milestone it has yet to announce.
Growth slows as spending commitments loom
The bigger concern is not just slower growth, but what it means for the massive infrastructure buildout OpenAI has already committed to.
Sarah Friar, OpenAI’s chief financial officer, warned internally that the company may struggle to meet those obligations if revenue does not accelerate.
According to the report, she told executives OpenAI might not be able to “pay for future computing contracts if revenue doesn’t grow fast enough.”
That tension is starting to show up in how the business is being managed, with board members reportedly taking a magnifying glass to data center deals and spending plans as costs shoot skyward and growth becomes way less predictable.
OpenAI has spent aggressively to secure compute capacity, including a multiyear partnership with Oracle and broader commitments totaling hundreds of billions of dollars.
Those deals were made when ChatGPT’s growth looked nearly unlimited. That pace has since cooled.
Competition and expectations reset
OpenAI is pushing back on the narrative, saying in a statement that the business is “firing on all cylinders” and dismissing suggestions of internal disagreement over infrastructure strategy. Chief executive Sam Altman and Friar also said claims they are not aligned are “ridiculous.”
At the same time, competition is peeking out from behind the bushes. Rivals like Anthropic have quietly been gaining traction, particularly in enterprise and developer use cases. Other platforms continue to pull users into their own ecosystems, which is spreading demand across more providers.
That does not mean AI usage is shrinking; it just means the growth is getting redistributed, and the expectations tied to one company may have gotten ahead of reality.
For companies building around this ecosystem, spending is still happening, but it is being watched more closely. Growth is still there, just less predictable than it looked a year ago.
What MSPs and resellers need to know
For channel partners, the shift signals a more measured AI spending environment where large-scale infrastructure bets may face closer scrutiny and longer return timelines.
Watch: We spoke with SotaTek US CEO MK Tong about AI infrastructure projects and how MSPs can provide value in the AI era.
MSPs, resellers, and cloud partners building services around hyperscaler and AI model ecosystems could see customers slow or phase deployments, prioritizing cost control and proven use cases over rapid expansion.
At the same time, this creates an opening for partners to differentiate on optimization—helping clients right-size compute, manage AI workloads efficiently, and navigate a more fragmented vendor landscape as demand spreads beyond a single dominant provider.
Many of those trends are not new to partners, who have seen similar market maturation across cloud and security, for example. Now, AI demand seems poised for a similar trajectory.
Dell, NVIDIA, and Elastic are tightening up the infrastructure side with updates to the Dell AI Data Platform, focused on reliably getting AI workloads into production. That kind of work starts to matter a lot more when growth expectations wobble, because suddenly efficiency and where you spend on compute come into sharper focus.