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Sometime in the next twelve months, an Anthropic director will log onto an earnings call and explain to a room full of analysts why quarterly revenue missed expectations because the board chose safety over deployment. The question will be some version of “walk us through the tradeoff” and the answer will have no precedent. That conversation has never happened at public-company scale. It will, and nobody knows what happens next.
Over 190 companies are waiting to go public in 2026, but only two raise governance questions the market has no framework for — and the confidential filing that kicked off the race is already behind them. Anthropic is a Delaware Public Benefit Corporation with a Long-Term Benefit Trust that can override shareholder preferences. OpenAI uses a capped-profit model where returns are contractually limited and a nonprofit board holds ultimate control. Neither fits the governance template that public markets are built to price.
Traditional tech IPOs (Google, Meta, Snap) used dual-class shares to preserve founder control over commercial strategy. AI governance adds a dimension that dual-class structures never addressed: legally enforceable mission constraints on profit. Here is what each structure looks like, how they compare, and how to think about the gap between what listing standards assume and what these companies have hard-coded into their charters — the governance puzzle at the centre of the public-market experiment unfolding across the AI industry.
What does Anthropic’s Public Benefit Corporation status mean for its IPO?
Anthropic is organised as a Delaware Public Benefit Corporation, which means its directors have a statutory duty to balance shareholder returns against the company’s stated public benefit: the safe development of artificial general intelligence. They are not required to maximise shareholder value. Under Delaware law (DGCL §§361–368), this duty is enforceable. Shareholders owning 2% or $2 million in stock can bring derivative suits alleging the board failed to balance pecuniary and benefit interests.
The Long-Term Benefit Trust adds another layer. Five trustees can recruit and remove board members if they determine the company is deviating from its safety mission. Combined with a staggered board and supermajority voting requirements for structural changes, Anthropic’s governance creates a set of checks that no public company has.
If you are accustomed to annual director elections, majority voting, and shareholder proposal rights, you will find this structure more restrictive than most tech IPOs of the last decade. The question is whether you price that restriction as a protective mechanism or a liability.
Anthropic’s PBC vs OpenAI’s capped-profit structure: which is more investor-friendly?
The two structures solve the same problem differently. Anthropic’s approach is directional: the board must balance profit against safety, with the benefit trust providing enforcement. OpenAI’s approach is quantitative: investor returns are capped at a multiple of investment (reportedly 100x). Excess profits flow to the nonprofit parent.
Anthropic’s PBC offers standard equity returns but introduces governance risk. The board can legally refuse a lucrative deployment on safety grounds, and the Long-Term Benefit Trust can replace directors who prioritise profit over mission. OpenAI’s capped-profit structure offers governance certainty at the cost of a hard upside ceiling. Its nonprofit board has ultimate authority over the for-profit subsidiary regardless of investor preferences, and the operating agreement states explicitly that the mission “takes precedence over any obligation to generate a profit.”
SpaceX provides the closest precedent. Its dual-class structure concentrates 85% of voting power with Elon Musk, making it a “controlled company” that the market has accepted with a governance discount. But SpaceX’s mission (colonise Mars) carries no tradeoff against quarterly revenue. AI governance introduces a safety-versus-revenue tension that SpaceX never had to navigate.
Neither structure is clearly “more investor-friendly.” They represent different risk profiles. Anthropic offers uncapped returns with governance risk; OpenAI offers governance certainty with capped returns. The market has no precedent for pricing either one.
How do AI governance mechanisms compare to traditional public company governance under exchange listing standards?
NYSE and Nasdaq listing rules require majority-independent boards, independent audit committees, and shareholder approval for equity compensation plans. None address what happens when a company’s charter requires the board to prioritise something other than shareholder returns.
The gap is visible in the proxy advisor vacuum. ISS and Glass Lewis have voting guidelines for dual-class structures and board independence, but neither has published a framework for evaluating PBC boards or capped-profit governance. If you rely on these firms for voting recommendations, you are left without a standardised assessment tool. 67% of US investors evaluate AI issues on a case-by-case basis, and 29% have no benchmarks or voting policies for AI at all.
54% of S&P 100 companies now disclose board-level AI oversight in their proxy statements. But that standard addresses how boards monitor AI risk, not how AI companies are governed. The governance question is upstream of the oversight question. The SEC Investor Advisory Committee recommended in late 2025 that issuers disclose board oversight mechanisms for AI, but the focus is on risk disclosure, not structural governance design. The gap between what listing standards assume and what AI governance requires is wide. What happens when that gap meets quarterly earnings pressure?
What happens when an AI company legally built to prioritise safety has to answer to Wall Street?
The pressure will arrive through multiple channels at once. Activist investors will demand strategy changes when safety decisions reduce revenue. Proxy advisory firms will issue voting recommendations against directors who prioritise mission over returns. Analysts will downgrade following quarters driven by mission-constrained decisions.
Standard public-company governance assumes the board’s fiduciary duty runs to shareholders first. A PBC board must articulate why balancing against the public benefit serves long-term shareholder value, and no company has had to deliver that narrative at public-company scale. The closest benchmark is Once Upon a Farm, a small PBC whose S-1 risk factors (discussed in detail below) explicitly address the tension between public benefit duties and shareholder value. Once Upon a Farm is far smaller than any AI lab, but its S-1 remains the only PBC filing that grapples explicitly with the fiduciary tension, and the language it uses is the disclosure floor, not the ceiling.
Quarterly disclosure becomes a stress test. Safety incidents, compute allocation decisions, and revenue concentration will be visible in ways they never were as a private company. The governance structure determines who controls the narrative around those disclosures. If the structure gives you enough information to price what you are buying, the market can accept a governance discount the way it accepted dual-class discounts for Google and Meta. If it does not, the discount becomes a crisis.
How can investors assess whether an AI lab’s governance protects shareholder interests?
You need to assess AI governance across three dimensions, and none of them appear on a standard governance checklist.
First, structural durability. Can the governance mechanism survive an activist campaign? Dual-class shares, staggered boards, and supermajority provisions are the standard toolkit for activist-proofing. AI companies layer mission constraints on top. You need to evaluate whether these layers create barriers to shareholder influence that go beyond what dual-class structures have delivered in the past.
Second, the safety-versus-revenue tradeoff. Model scenarios where a lucrative deployment is blocked by governance. A defence contract refused on ethical grounds. A commercial model release delayed for safety testing. What revenue could the company forgo, and how does the market price that risk? Anthropic’s own forecast puts the probability of a $100 million-plus defence contract by May 2027 at just 3%, reflecting governance constraints interacting directly with revenue opportunity.
Third, transparency. The governance structure determines who controls the narrative when safety decisions become quarterly disclosures. You need enough information rights to make informed decisions. Dual-class shares address founder control, not mission constraints. The gap between those two purposes is where governance risk lives. Here is how to spot that risk in an S-1 filing — and the capital event reshaping the AI industry makes this skill more urgent than any prior tech cycle has.
What governance red flags should investors look for in an AI company preparing to go public?
Five red flags separate mission-preserving governance from accountability-evading opacity.
First, information rights. If the governance structure gives the board or a trust authority to block commercial decisions without requiring disclosure of the reasoning, you cannot price the risk. Second, director removal barriers. If you cannot remove directors who consistently prioritise mission over returns, the structure has no accountability mechanism. SpaceX’s governance shows what extreme accountability failure looks like: with 85% voting control, removing the CEO requires a majority of shares he alone controls.
Third, undefined benefit scope. If the public benefit purpose is stated in broad, aspirational terms without specific, measurable commitments, the board has unlimited discretion to justify any decision as mission-aligned. Fourth, no sunset provisions. If mission-constraint mechanisms are permanent rather than subject to periodic shareholder reapproval, there is no market check on whether the constraints still serve their purpose.
Fifth, S-1 risk factor language. Once Upon a Farm’s S-1 sets the disclosure benchmark: it states its directors are “not merely permitted, but obligated, to consider our specific public benefit” and that “[our] duty to balance a variety of interests may result in actions that do not maximise stockholder value.” Any AI lab S-1 with weaker disclosure than a baby food company leaves you with less information to price governance risk.
Whether AI governance survives the public markets depends on whether each company’s transparency and accountability mechanisms give you enough information to price the mission-vs-revenue tradeoff. The structures will survive if they produce enough disclosure for the market to do its job. They will break if they use mission constraints as a shield against accountability.
As the SpaceX precedent shows, the market accepts governance discounts, but only when it can see what it is pricing. The proxy advisor vacuum means you must build your own evaluation framework, and the three dimensions (durability, tradeoff, transparency) are the starting point — but governance is just one axis of second-order effects that ripple far beyond governance.
Whether AI governance survives comes down to an informational question: can you see enough to price what you are buying? How governance risk factors into a broader evaluation framework is the question every AI IPO investor will need to answer.
Frequently Asked Questions
Can Anthropic’s Long-Term Benefit Trust actually block a takeover bid?
Yes. The Long-Term Benefit Trust has the authority to recruit and remove board members if it determines the company is deviating from its safety mission. In a hostile takeover scenario, the trust could replace directors who support the acquisition with trustees who oppose it, effectively blocking any bid it deems inconsistent with Anthropic’s public benefit purpose. Combined with the staggered board and supermajority voting thresholds, the trust creates a takeover defence that is structurally stronger than any poison pill a traditional public company could deploy.
Is the 100x return cap on OpenAI investments generous or restrictive?
It depends entirely on what you compare it to. A 100x return on a late-stage investment implies OpenAI must reach roughly a $10 trillion valuation for its most recent investors to hit the cap, which makes the ceiling appear theoretical rather than practical. But as a structural feature, the cap means investors can never capture tail-risk upside of the kind that made early Google and Meta shareholders billionaires many times over. The cap is generous relative to most venture outcomes and restrictive relative to what uncapped equity in a world-changing technology company has historically delivered.
What legal test does a Delaware court apply to determine if a PBC board properly balanced its duties?
Delaware courts apply a two-part test under DGCL section 365. First, the court examines whether the board’s decision was rationally related to the corporation’s stated public benefit. Second, it assesses whether the decision was informed and disinterested, applying the business judgment rule. So far, no Delaware court has adjudicated a PBC balancing claim at trial, which means every AI governance dispute would be litigating on uncharted ground. Directors get significant deference, but the rational-relationship threshold is not a blank cheque.
Could Anthropic ever remove its PBC status if shareholders wanted it to?
Not easily. Converting from a Delaware Public Benefit Corporation to a standard corporation requires approval from holders of at least two-thirds of outstanding shares, the same supermajority threshold that protects the structure in the first place. The Long-Term Benefit Trust’s board influence makes assembling that two-thirds majority extraordinarily difficult. More fundamentally, the trust was designed precisely to prevent shareholder pressure from unwinding the mission constraints, and it would almost certainly mobilise against any conversion effort.
Has any public benefit corporation ever been acquired against its board’s wishes?
Not at Anthropic’s scale. Small PBCs have been acquired, but these were friendly transactions where the acquirer committed to maintaining the benefit purpose post-closing. No hostile takeover of a PBC has been tested in Delaware courts, and no PBC with a trust-based governance override like Anthropic’s has ever faced an unsolicited bid. The absence of precedent is itself a governance risk: nobody knows whether a Delaware court would prioritise shareholder value maximisation or public benefit preservation in a contested transaction.
What happens to OpenAI’s capped-profit structure if the company needs more capital than the cap allows?
OpenAI would need to restructure, and doing so mid-IPO would be a governance crisis. The capped-profit subsidiary’s contractual terms are embedded in its operating agreement, and modifying them would require consent from existing investors who accepted the cap as part of their bargain. If OpenAI hit the cap and still needed capital, it could theoretically raise debt, create a new uncapped vehicle, or negotiate a waiver from investors, but each path introduces legal complexity and potential litigation from parties who prefer the original terms.
How do European exchanges treat public benefit corporations compared to US exchanges?
They do not recognise the structure at all. European corporate law does not have an equivalent to Delaware’s PBC, and exchanges in London, Amsterdam, and Frankfurt have no listing rules addressing mission-constrained governance. An AI lab listing in Europe would either need to incorporate locally under a structure that lacks the same statutory protection or list as a foreign private issuer while explaining to European institutional investors why their governance expectations about shareholder primacy do not apply. The governance gap is wider in Europe than in the US.
Could the SEC require additional governance disclosures from AI companies going public?
Yes, and it appears to be moving in that direction. The SEC Investor Advisory Committee recommended in late 2025 that issuers disclose board oversight mechanisms for AI, but the current focus is on how traditional companies monitor AI risk, not on the structural governance of AI companies themselves. The next logical step is S-1 disclosure requirements that force AI labs to quantify the safety-versus-revenue tradeoff in specific deployment scenarios. That would transform governance from a theoretical concern into a set of priced, disclosable risks.
Are there other AI labs with governance models that split the difference between Anthropic and OpenAI?
Yes, but none have announced IPO plans at comparable scale. Safe Superintelligence Inc. and several European labs use nonprofit or charitable structures with commercial subsidiaries, while Google DeepMind operates inside Alphabet’s standard corporate governance with an internal ethics review framework. The critical distinction is enforceability: a voluntary ethics board can be dissolved by management, while Anthropic’s benefit trust is a structural constraint that cannot be removed without a supermajority shareholder vote. Market participants are watching whether any third model emerges during the current pre-IPO pipeline.
What recourse do OpenAI investors have if the nonprofit board makes decisions they disagree with?
Very little. OpenAI’s capped-profit subsidiary is governed by a nonprofit board whose fiduciary duty runs to the nonprofit’s charitable mission, not to the subsidiary’s investors. Investors accepted this arrangement contractually when they bought in, and the operating agreement explicitly subordinates their interests to the nonprofit’s determination of what serves humanity. The only available challenge would be to argue the board acted outside its authority under the operating agreement itself, a narrow and difficult claim that offers no remedy for ordinary business disagreements.
