OpenAI is starting to slow down: from 'computing power at any cost' to 'calculating the accounts before expanding', the strategy before the IPO has clearly changed.

If the most distinct label for OpenAI in the past period was "charging forward regardless of cost for computing power," the signals released by the company recently have been markedly different. Sam Altman's remarks at the U.S. Infrastructure Summit have made this shift quite plain: building data centers is not an easy task; the larger the scale, the more variables there are, and any single point of failure could impact the overall progress. The data center campus in Abilene, Texas, encountering extreme weather and experiencing brief service interruptions is just a microcosm; supply chain pressures, construction cycles, and delivery cadence—these seemingly backend operational realities are gradually pulling OpenAI back onto the track of "must be pragmatic." For a company renowned for its technological narrative and capital imagination, this change is not merely an operational adjustment but more like a rebalancing of strategic focus.

More crucially, what OpenAI now faces is not a simple technological race but a "dress rehearsal" for the public market. As a company with IPO expectations, it must shift from the high-growth logic more characteristic of the private market to the financial discipline and sustainability logic more valued by the public market. The last funding round pushed OpenAI's valuation to $730 billion, and the market will naturally scrutinize it within a stricter framework: you can tell the long-term story of AI, but you must also explain how the massive capital expenditures, ultra-high computing power procurement, and revenue growth form a closed loop. It is precisely for this reason that external controversy over OpenAI's previous series of large-scale infrastructure commitments continues to ferment. Altman previously hinted that the company might commit to investing around $1.4 trillion over the next eight years, while the company's annual revenue for 2024 was only $13.1 billion. This stark contrast easily reminds the market of the vendor financing model from the late 1990s and keeps discussions about an "AI bubble" simmering. Daniel Newman of Futurum Group put it bluntly: the market may not pay for "reckless growth and spending"; investors prefer to see revenue growth matching the scale of expenditures, which is also the core context for OpenAI's current strategic adjustment.

Therefore, OpenAI's current change is not about "not expanding" but about "changing the way it expands." Based on public information, the company has begun shifting from its previously more aggressive self-build approach to a resource integration route that relies more on external partners. OpenAI currently does not own its own data centers and is highly unlikely to move towards a heavy-asset self-build model in the foreseeable future, instead relying more on cloud and infrastructure partners like Oracle and Amazon to obtain computing power. This choice is fundamentally pragmatic: training and running AI models require massive amounts of chips, computing power, memory, and energy. Any company wanting to remain competitive must first solve the resource supply problem. It's just that OpenAI's past approach was more like "putting ambition out there first," while now it's more like "securing computing power first, then controlling the pace." Last November, Altman publicly mentioned that computing power constraints forced OpenAI and other companies to impose rate limits on products, preventing many new features and models from rolling out at the desired pace. By this year, the company's internal and external communications have placed greater emphasis on "focus" and "execution," particularly in advancing business around high-productivity application scenarios. OpenAI's declaration of a "red alert" last December and Fei-Fei Li's emphasis on maintaining focus in enterprise business during an all-hands meeting earlier this month, when viewed together, actually point to the same thing: OpenAI is shifting from "competing on scale, speed, and imagination" to "competing on efficiency, discipline, and delivery."

Behind this lies an even more representative change: the evolution of the relationship between OpenAI and NVIDIA. Last September, NVIDIA announced it would invest up to $100 billion in OpenAI over the coming years, tied to OpenAI's technology deployment and usage. At the time, OpenAI also stated plans to deploy at least 10 gigawatts of NVIDIA systems. This deal once shook the market and further fueled concerns about an AI infrastructure bubble. Analysts pointed out at the time that this transaction structure was reminiscent of the vendor financing model from the late-1990s internet bubble. Subsequently, the market continuously speculated about the real progress of this partnership, and NVIDIA also cautioned in filings that the related transactions might not ultimately materialize. Recently, Jensen Huang's tone has noticeably cooled; he even suggested that the opportunity to invest $100 billion in OpenAI might be "not in the plan." The latest investment is no longer strongly tied to specific deployment milestones, differing from the previously publicized transaction structure. To some extent, this also illustrates a fact: while OpenAI's capital story continues, its narrative logic has begun shifting from "infinitely amplifying expectations" to "proving itself more cautiously."

From an operational perspective, this shift is understandable. Over the past year or so, OpenAI has pushed itself to an extremely high starting point: it must maintain product leadership while staying competitive against Anthropic, Google, and more AI model and application companies; it must continuously acquire more computing power while avoiding further amplification of capital market concerns about runaway spending; it must articulate a sufficiently large future vision while convincing investors that the company is not simply built on burning cash. Newman's statement from Futurum Group, "This is a race," actually captures the industry's current state. OpenAI today is not slowing down but adjusting its running style: in the past, it was run first, talk later; now, it's run while keeping accounts. The problem is, competition in the AI industry waits for no one. Whether OpenAI can find a balance between cost control and maintaining growth is what will truly determine the quality of its IPO story.