OpenAI is reportedly preparing for a landmark initial public offering (IPO) that could value the company at up to $1 trillion, making it one of the largest IPOs in history.

The filing could come as early as the second half of 2026, with a potential listing by 2027, as OpenAI looks to expand beyond its private funding base and tap public markets for growth capital.

The move follows a corporate restructuring that established the nonprofit OpenAI Foundation and reduced Microsoft’s ownership to around 27%, giving Sam Altman’s company greater strategic and operational independence.

This IPO represents more than just a record-breaking valuation; it marks the beginning of OpenAI’s next phase of industrial growth. With rising compute demands and a heavy reliance on Nvidia’s hardware, the company is seeking new capital to build its own energy-efficient infrastructure and diversify its chip supply chain.

In essence, OpenAI’s potential $1 trillion IPO isn’t just about valuation—it’s about reshaping the structure and scale of the company for the future of artificial intelligence.

Building the War Chest: IPO, Structure, and AGI Infrastructure

As OpenAI prepares for its public listing, the company is also redefining its financial and organizational foundation to support its next phase of growth.

This isn’t just about achieving a record valuation – it’s about securing the capital and building the infrastructure required to fuel the race toward artificial general intelligence (AGI).

OpenAI’s restructuring and forthcoming IPO represent the foundation of a long-term strategy: to create the resources, autonomy, and scale needed to lead the next era of intelligent computing.

A Corporate Reset for Capital and Control

In recent weeks, OpenAI completed a sweeping corporate restructuring that established the OpenAI Foundation, a nonprofit entity designed to anchor the company’s mission around the safe and ethical development of artificial general intelligence (AGI).

The Foundation now holds a 26% equity stake in the for-profit OpenAI Group PBC, a public benefit corporation structured to balance two often competing forces – mission oversight and capital flexibility.

At the same time, Microsoft’s ownership has been reduced to around 27%, signaling OpenAI’s clear intent to lessen its dependence on a single strategic partner and broaden its governance base.

This new hybrid model provides OpenAI with the flexibility to raise capital from public markets while maintaining its nonprofit influence at the board level.

However, it also invites a key question: how will OpenAI reconcile the commercial pressures of a trillion-dollar enterprise with its foundational commitment to developing AGI safely and responsibly?

Funding the AGI Future (and Its Backers)

CEO Sam Altman’s vision for OpenAI will require massive investment, potentially hundreds of billions of dollars, to expand compute capacity and secure reliable renewable energy sources.

Looking ahead, OpenAI may also develop its own custom AI chips to reduce dependence on suppliers like Nvidia and strengthen control over its hardware stack. It’s an ambitious step, but one that could be essential to sustaining the race toward AGI.

An IPO would provide OpenAI with the capital it needs to accelerate its long-term vision, while also rewarding major early backers, including SoftBank, Thrive Capital, and Abu Dhabi’s MGX.

With revenues projected to reach $20 billion but losses climbing due to the soaring cost of Nvidia hardware, going public is both a strategic necessity and a natural next step.

Ultimately, OpenAI aims to build a vertically integrated AI economy—one that unites chips, compute, and energy into a self-sustaining industrial ecosystem capable of powering the next era of intelligent technology.

Breaking Away from Nvidia: The Cost Efficiency Imperative

As the IPO comes into view, one of the clearest signals from OpenAI’s next phase is a push to escape the cost and energy bottlenecks tied to its current hardware platform.

The strategy centers on both reducing dependency on Nvidia’s GPU monopoly (and its rising costs), as well as improving efficiency in infrastructure built for AGI-scale demands.

Nvidia’s Grip and the Energy Equation

Nvidia’s GPUs remain the backbone of most AI training operations, including those of OpenAI. 

However, these GPUs come with steep costs and fast-growing energy demands. Supply-chain tightness and per-unit price increases have amplified these operating expenses, while US power grids strain under the scale of these large AI training clusters.

Chinese competitors, such as DeepSeek, appear to be outpacing Nvidia’s GPUs in terms of energy efficiency. This highlights a strategic gap, and if OpenAI wants to scale successfully, it needs to address this gap.

The Alternatives: AMD and Google in Play

This October, OpenAI entered into a multi-gigawatt deal with AMD (Instinct MI450 and future generations), on track for a 1 GW deployment in the second half of 2026, and up to 6 GW over time.

At the same time, the company is exploring Google’s Tensor Processing Units (TPUs) and other accelerator platforms to further diversify its compute stack – and, ideally, optimize its energy costs.

The shift toward a more varied compute ecosystem could increase OpenAI’s GFLOPS per watt, while reducing its cost per watt and mitigating its supplier risk. Overall, it could position OpenAI as a more resilient infrastructure player, not just an LLM model operator.

The Bigger Picture: AI’s Next Market Boom

OpenAI’s IPO may be the culmination of one wave – and the spark of the next. As infrastructure, software, and energy converge, companies moving into publicly traded markets could redefine how investors access the growing AI narrative.

The Market Catalyst and Investor Mania

AI stocks are surging – and have been for much of the last two years. In fact, Nvidia recently reached a whopping $5T market capitalization: a historic milestone not just in the tech sector, but for any company.

Meanwhile, CoreWeave, an AI-infrastructure provider, has seen its share prices rise rapidly since its IPO in March, currently trading at $126 – over three times its price at launch.

If OpenAI’s IPO unfolds smoothly, it could ignite the next wave of AI investment, positioning the company as the software counterpart to Nvidia’s hardware dominance. Together, they would represent a kind of “completion” of the AI ecosystem that investors have long been anticipating.

A Global Realignment in AI Infrastructure

OpenAI’s public debut would likely act as a catalyst for competition among chipmakers, cloud providers, and energy firms, all racing to deliver the lowest cost per watt for AGI-scale compute.

The center of gravity in the AI space may shift away from Nvidia (the dominant GPU supplier) toward vertically integrated ecosystem players with hardware, compute, and energy in-house.

This global reshuffling echoes broader geopolitical dynamics, as nations like Saudi Arabia pursue ambitious AI strategies positioned between U.S. and Chinese interests, leveraging their energy resources to become major players in the next era of artificial intelligence.

The center of gravity in the AI space may see a shift away from Nvidia – today’s GPU supply’s dominant force – and toward vertically integrated ecosystem players with hardware, compute, and energy in-house. At the very least, that’s what OpenAI envisions.

Profit, Mission, and the Future of AI

OpenAI’s potential $1 trillion IPO could mark a defining moment in its evolution, from a research pioneer into a full-scale industrial powerhouse.

Yet the move raises a critical question: can a publicly traded company truly uphold its mission of “safe AGI” when market expectations demand relentless growth?

The debate over ethical AI is intensifying across industries, from corporations pursuing AGI to governments deploying AI for surveillance, as seen in ICE’s use of AI to monitor social media activity.

As OpenAI channels public capital into more efficient hardware and energy systems, it faces the complex challenge of balancing innovation with ethical responsibility.

If successful, the company could not only lessen its dependence on Nvidia but also redefine what true AI leadership means, measured not just by model intelligence but by efficiency, autonomy, and the ability to balance moral restraint with profit.