The rapid evolution of artificial intelligence company compensation, from capped profit interests to public benefit corporation equity to compute allocations, has outpaced the analytical frameworks most damages experts currently utilize. This article examines the structural features of AI executive pay, the valuation challenges they present, and the methodological approaches best suited to economic loss analysis in this emerging area. The analysis is presented for informational purposes and does not constitute legal advice.
On April 27, 2026, a federal jury was seated in Oakland, California to hear Musk v. Altman et al., a case in which Elon Musk, co-founder of OpenAI, seeks as much as $150 billion in damages from OpenAI and its chief executive Sam Altman, alleging breach of charitable trust and unjust enrichment arising from the company’s conversion from a nonprofit to a public benefit corporation (“PBC”).1 The jury returned a verdict in Altman’s favor, but on procedural grounds, ruling that Musk’s claims were barred by the statute of limitations without reaching the merits of the underlying allegations.2 That outcome, while decisive for the parties, leaves unresolved the set of economic questions the trial placed into sharp public focus: how should the equity, profit interests, and non-cash compensation held by departing or transitioning AI executives be valued in an adversarial proceeding?
The timing is significant for damages practitioners. OpenAI completed its PBC restructuring on October 28, 2025,3 converting a compensation architecture built around capped profit participation units (“PPUs”) into standard equity. As AI companies continue to grow, restructure, and shed executives, forensic economists will be called upon with increasing frequency to value instruments that resist standard analytical approaches.
This article identifies the principal structural features of AI executive compensation that differentiate it from conventional corporate pay, examines the specific valuation challenges those features create, surveys emerging dispute scenarios grounded in documented industry developments, and offers methodological guidance rooted in established professional standards.
I. THE SHIFTING ARCHITECTURE OF AI EXECUTIVE PAY
Standard corporate compensation for senior executives at publicly traded companies follows a well-established template: base salary, annual cash bonus, and long-term equity incentives typically denominated in publicly traded shares.4 Major AI companies have departed significantly from this model, creating instruments that require careful unpacking before economic damages can be assessed.
Capped Profit Interests: The PPU Structure
The most distinctive compensation instrument in recent AI industry history is the Profit Participation Unit, or PPU, which OpenAI used as its primary equity-equivalent instrument prior to its October 2025 PBC conversion. At OpenAI, compensation has included profit participation units (PPUs), which are structured as capped, profit-linked instruments rather than traditional equity. Public information indicates that these awards are subject to payout limits and vesting schedules, though specific grant sizes, caps, and lock-up provisions are not publicly disclosed.5 In January 2026, OpenAI transitioned its compensation structure to standard restricted stock units (“RSUs”).6 OpenAI’s PPU structure was distinctive among major AI laboratories. Anthropic, organized as a public benefit corporation, compensates employees using conventional startup equity instruments, including stock options (ISOs and NSOs) and, increasingly for later-stage hires, restricted stock units (RSUs), rather than capped profit-interest structures.7
The PBC Conversion and Its Equity Implications
When OpenAI completed its restructuring on October 28, 2025, the company’s for-profit subsidiary became OpenAI Group PBC, a public benefit corporation required by its charter to advance the company’s stated mission while operating commercially. The restructuring allocated approximately 26% of the new entity’s equity to employees, including former employees, while Microsoft received approximately 27% and the nonprofit OpenAI Foundation retained 26%.8 The conversion eliminated the profit cap embedded in the PPU structure, allowing equity holders to participate without a ceiling in any future appreciation. For a damages expert, this transition creates a discontinuity: the economic value of a PPU and the economic value of an equivalent RSU in the post-conversion PBC are measured by fundamentally different analytical frameworks.
Compute Allocations as a Compensation Component
A second structural development with direct damages implications is the emergence of compute allocation, access to GPU clusters and AI inference capacity, as a substantive component of executive and engineer compensation. Industry commentators describe compute access as a “fourth pillar” of compensation alongside cash, equity, and annual bonuses, with the amount of inference compute available to an engineer increasingly determining that engineer’s productivity.9 At current market rates, NVIDIA H100 GPU instances range from approximately $1.38 per GPU-hour on budget cloud providers to $11.01 per GPU-hour on major hyperscalers, including Google Cloud, with AWS pricing near $6.8.10 Tax treatment of personal compute allocations remains unsettled, complicating both compensation design and retrospective economic quantification.
The trend extends beyond OpenAI. Industry reporting identifies compute access as an emerging compensation element across AI laboratories broadly, including Anthropic, reflecting the sector-wide scarcity of GPU capacity among organizations building large-scale models.11 For damages experts, the challenge is compounded where compute benefits are informal or undocumented: an allocation offered verbally, customarily, or embedded in an employment letter without precise specifications may be difficult to value retrospectively, yet may represent substantial economic value at current GPU market rates.
Compensation Quantum for Senior AI Leaders
Equity compensation packages for senior AI leaders at growth-stage AI companies routinely range from $4 million to $15 million, with total compensation weighted heavily toward equity.12 AI-specific leadership roles command approximately 10% higher total compensation than comparable non-AI engineering leadership positions at equivalent organizational stages.13 At mature public companies, senior AI leaders may receive long-term equity awards approaching $30 million in total value.14
For a damages expert, these figures establish an important methodological baseline: equity constitutes the economically dominant component of senior AI compensation at growth-stage companies, often representing the majority of total compensation value. Disputes over withheld, unvested, or improperly converted equity therefore implicate the largest share of a claimant’s economic loss, and the defensibility of the damages calculation will turn primarily on the methodology used to value illiquid private-company equity at a specific historical date, not on the cash component, which is typically ascertainable from payroll records and offer letters.
II. VALUATION CHALLENGES FOR ECONOMIC EXPERTS
The principal difficulty in valuing AI executive equity for damages purposes is not conceptual but empirical: the data inputs are thin, volatile, and frequently inconsistent with one another.
Valuation Velocity
The speed at which leading AI companies have appreciated is without close historical precedent in the private markets. Anthropic, the maker of the Claude AI assistant, illustrates the challenge. Its March 2025 financing valued the company at $61.5 billion. By September 2025, a new round valued it at $183 billion. A further round closed February 12, 2026, at a $380 billion post-money valuation.15 As of late April 2026, Anthropic was reportedly receiving preemptive offers for a new round at valuations ranging from $850 billion to $900 billion, a more than thirteenfold increase in approximately thirteen months.16
OpenAI’s trajectory mirrors this pattern. A secondary share sale in October 2025 established a $500 billion post-money valuation.17 The close of a $122 billion primary round on March 31, 2026, pushed the post-money valuation to $852 billion.18 For damages experts tasked with constructing a “but-for” world valuation, the selection of a relevant valuation date and the economic justification for that date carry extraordinary consequences in this environment.
Thin Secondary Markets and Price Discovery
For a damages expert, secondary market transactions have a critical role in private equity valuation: they represent the most direct observable evidence of what arm’s-length buyers and sellers assign as market value for a private company’s equity at a specific date. Unlike income-based approaches, which require contested revenue and growth projections, secondary transactions reflect actual market-clearing prices. When such markets are thin, however, observed prices may diverge materially from intrinsic value, widening the defensible range of any damages estimate and increasing the analytical burden on the expert to document the basis for any price adjustment applied.
Secondary market trading in AI company shares has expanded dramatically but remains structurally thin relative to total equity outstanding. AI-related transactions on Forge Global’s secondary marketplace grew from approximately 2% of total platform volume in 2022 to 44% of volume in 2025, representing a 3,860% increase in absolute transaction activity.19 Nasdaq Private Market reported that its total settled secondary trade value more than doubled in 2025, rising from $372 million to $673 million. Despite this growth, demand continues to outstrip supply: the OpenAI employee tender offer in October 2025, in which current and former employees sold $6.6 billion in shares at a $500 billion valuation, reportedly left approximately $4 billion in unfulfilled buyer demand.21
The Absence of Comparable Public Companies
Comparable company analysis (known in valuation practice as the market approach) is a foundational method for establishing the value of a private entity by reference to how the market prices businesses with similar characteristics. A damages expert identifies publicly traded companies with comparable business models, growth profiles, and capital structures, then uses those companies’ market-implied valuation multiples to calibrate a value estimate. This approach is valued in litigation because it grounds the analysis in observable, arm’s-length market data, making it more transparent and less susceptible to challenge than purely projection-based alternatives. When no close public comparables exist, experts must rely more heavily on income-based approaches that are more sensitive to contested assumptions, increasing the range of plausible damages estimates and placing greater weight on the expert’s individual judgment calls.
In the AI sector, however, that standard set of comparable firms does not exist. As of 2025, only six private companies globally were valued at $100 billion or more, and four were AI-focused: OpenAI, Anthropic, xAI, and Databricks.22 There are no close public-market analogs for any of these entities. Cloud infrastructure companies, software platforms, and semiconductor manufacturers share surface characteristics but diverge in growth rates, capital intensity, and margin profiles in ways that substantially limit their use as comparables for private AI equity valuation.
III. SPECIFIC DAMAGES SCENARIOS EMERGING IN PRACTICE
The combination of novel equity instruments, rapid valuation appreciation, and high-stakes leadership transitions creates a predictable taxonomy of economic disputes. Some have already materialized in active litigation; others are structurally foreseeable.
The Equity Conversion Dispute: Musk v. Altman
Musk v. Altman et al., concluded on May 18, 2026, when a federal jury ruled in Altman’s favor on statute of limitations grounds, finding that Musk had filed his claims too late without reaching the merits of the underlying allegations. The case remains the most prominent litigation involving AI executive equity. Musk’s claims of breach of charitable trust and unjust enrichment alleged that OpenAI’s nonprofit-to-PBC conversion enriched Altman, Brockman, and other senior executives by eliminating the profit caps that governed their compensation under the prior structure, with claimed damages ranging from $130 billion to $150 billion.23 Because the jury did not reach the merits, damages experts would have needed to evaluate, and on appeal or in future proceedings may still need to evaluate, under a counterfactual framework, what the economic value of senior executive holdings would have been had the nonprofit structure been preserved, an analysis requiring assumptions about both future profitability and the governance constraints that would have applied under the prior organizational form.
Structural Scenarios for Future Disputes
Beyond the Musk litigation, the structural features of AI executive pay create several recurring dispute patterns that damages practitioners should anticipate.
PPU-to-RSU Conversion Disputes. Executives or employees who departed OpenAI after the PBC conversion was announced but before their PPUs were converted to RSUs may face disputes over the economic value of their departed instruments. The transition from a capped profit interest (10×) to uncapped equity creates a step-change in value that depends critically on the date of departure and the applicable conversion methodology.
Milestone-Based Vesting Disputes. Where equity vests upon defined technical milestones (e.g., deployment of a specific AI model, achievement of a revenue threshold), disputes over whether the triggering condition was met require collaboration between damages economists and technical experts qualified to assess the AI system’s functional state at the relevant date.
Compute Allocation Disputes. As compute access is increasingly treated as compensation, the withdrawal or withholding of promised GPU resources may give rise to quantifiable economic loss claims. Calculating such a loss requires reference to current market-rate GPU pricing and an assessment of any productivity or revenue impact attributable to the constrained allocation.
Non-Compete Consideration. Senior AI executive departures commonly involve non-compete provisions. Valuing the economic consideration for a non-compete requires estimating expected earnings foregone in the restricted field during the applicable restriction period, an analysis that must account for the extraordinary compensation levels now prevailing in the sector.
CONCLUSION
The Musk v. Altman trial was, in structural terms, the opening act in a category of economic dispute that forensic economists will encounter with growing frequency. The AI industry’s combination of rapid valuation appreciation, novel compensation instruments, and high-stakes leadership transitions creates conditions under which executive equity disputes will be both common and analytically challenging. Damages experts who develop familiarity with capped profit interest structures, PBC equity conversions, compute-as-compensation frameworks, and the professional standards applicable to private AI equity valuation will be better positioned to provide rigorous, defensible economic analysis as these cases mature.
The methodological frameworks needed to address this work are not novel. What is new is the domain: a sector where valuations can change dramatically in a single quarter, where the compensation instruments are structurally novel, and where the factual record is being actively written by proceedings like Musk v. Altman, all of which underscores that analytical preparation is, for damages practitioners, a present-tense obligation.
Endnotes
1. NPR, “Musk vs. Altman: Tech CEOs head to court over the fate of OpenAI,” April 27, 2026, https://www.npr.org/2026/04/27/nx-s1-5795661/trial-openai-elon-musk-sam-altman; CNBC, “OpenAI trial day 2 takeaways: Musk testifies OpenAI was created as nonprofit to counter Google,” April 28, 2026, https://www.cnbc.com/2026/04/28/openai-trial-elon-musk-sam-altman-live-updates.html, Courthouse News Services, “Jury selection commences in Musk-Altman feud,” April 27, 2026, https://www.courthousenews.com/jury-selection-commences-in-musk-altman-feud/.
2. GeekWire, “Jury finds Musk waited too long to sue OpenAI and Microsoft, clearing defendants in landmark AI case,” May 18, 2026, https://www.geekwire.com/2026/jury-finds-musk-waited-too-long-to-sue-openai-and-microsoft-finding-defendants-not-liable-on-all-claims/.
3. CNBC, “OpenAI completes restructure, solidifying Microsoft as a major shareholder,” October 28, 2025, https://www.cnbc.com/2025/10/28/open-ai-for-profit-microsoft.html, OpenAI, “Built to benefit everyone,” October 28, 2025, https://openai.com/index/built-to-benefit-everyone/.
4. Kevin J. Murphy, Executive Compensation: Where We Are, and How We Got There, in Handbook of the Economics of Finance, Vol. 2A, at 211–356 (George Constantinides et al. eds., Elsevier 2013), https://www.sciencedirect.com/science/chapter/handbook/abs/pii/B9780444535948000045.
5. Levels.fyi, “OpenAI PPUs: How OpenAI’s unique equity compensation works,” https://www.levels.fyi/blog/openai-compensation.html, OpenAI, “OpenAI LP,” https://openai.com/our-structure, OpenAI, “OpenAI Charter,” https://openai.com/charter
6. Levels.fyi, “OpenAI PPUs: How OpenAI’s unique equity compensation works,” https://www.levels.fyi/blog/openai-compensation.html.
7. Business Insider, “How Anthropic is rewriting startup pay,” https://www.businessinsider.com/anthropic-rewriting-startup-pay-levels-2025-9, NAHC.io, “Anthropic Salary Overview: How Much Do Employees Get Paid,” https://www.nahc.io/blog/anthropic-salary-overview-how-much-do-employees-get-paid.
8. CNBC, “OpenAI completes restructure, solidifying Microsoft as a major shareholder,” October 28, 2025, https://www.cnbc.com/2025/10/28/open-ai-for-profit-microsoft.html; NBC News, “A nonprofit on top, billions below: How OpenAI’s new structure works,” https://www.nbcnews.com/tech/tech-news/openai-restructuring-company-structure-chatgpt-invest-own-rcna240138.
9. TechSpot, “Tech hiring evolves as candidates ask for AI compute alongside pay and perks,” https://www.techspot.com/news/111641-tech-hiring-evolves-candidates-ask-ai-compute-alongside.html; AI CERTs News, “Tech Talent Perks: Compute Credits Redefine AI Compensation,” https://www.aicerts.ai/news/tech-talent-perks-compute-credits-redefine-ai-compensation/.
10. ThunderCompute, “NVIDIA H100 Pricing (April 2026): Cheapest Cloud GPU Rates,” April 2026, https://www.thundercompute.com/blog/nvidia-h100-pricing.
11. TechSpot, “Tech hiring evolves as candidates ask for AI compute alongside pay and perks,” https://www.techspot.com/news/111641-tech-hiring-evolves-candidates-ask-ai-compute-alongside.html; AI CERTs News, “Tech Talent Perks: Compute Credits Redefine AI Compensation,” https://www.aicerts.ai/news/tech-talent-perks-compute-credits-redefine-ai-compensation/.
12. Riviera Partners, “AI Leader Pay in 2026: What Hundreds of Executive Searches Reveal About Compensation,” 2026, https://www.rivierapartners.com/insights/ai-leader-pay-in-2026-what-hundreds-of-executive-searches-reveal-about-compensation/.
13. Riviera Partners, “AI Leader Pay in 2026: What Hundreds of Executive Searches Reveal About Compensation,” 2026, https://www.rivierapartners.com/insights/ai-leader-pay-in-2026-what-hundreds-of-executive-searches-reveal-about-compensation/.
14. Riviera Partners, “AI Leader Pay in 2026: What Hundreds of Executive Searches Reveal About Compensation,” 2026, https://www.rivierapartners.com/insights/ai-leader-pay-in-2026-what-hundreds-of-executive-searches-reveal-about-compensation/.
15. CNBC, “Anthropic closes $30 billion funding round at $380 billion valuation,” February 12, 2026, https://www.cnbc.com/2026/02/12/anthropic-closes-30-billion-funding-round-at-380-billion-valuation.html; Tracxn, “Anthropic — 2026 Funding Rounds & List of Investors,” https://tracxn.com/d/companies/anthropic/__SzoxXDMin-NK5tKB7ks8yHr6S9Mz68pjVCzFEcGFZ08/funding-and-investors.
16. TechCrunch, “Sources: Anthropic could raise a new $50B round at a valuation of $900B,” April 29, 2026, https://techcrunch.com/2026/04/29/sources-anthropic-could-raise-a-new-50b-round-at-a-valuation-of-900b/.
17. CNBC, “OpenAI wraps $6.6 billion share sale at $500 billion valuation,” October 2, 2025, https://www.cnbc.com/2025/10/02/openai-share-sale-500-billion-valuation.html (subscription required).
18. Bloomberg, “OpenAI Valued at $852 Billion After Completing $122 Billion Round,” March 31, 2026, https://www.bloomberg.com/news/articles/2026-03-31/openai-valued-at-852-billion-after-completing-122-billion-round (subscription required); TechCrunch, “OpenAI, not yet public, raises $3B from retail investors in monster $122B fund raise,” March 31, 2026, https://techcrunch.com/2026/03/31/openai-not-yet-public-raises-3b-from-retail-investors-in-monster-122b-fund-raise/.
19. Forge Global, “How AI Shaped the Private Market & the Data Behind 2025’s Transformation,” 2025, https://forgeglobal.com/insights/how-ai-shaped-private-market-data-behind-2025-transformation/; Nasdaq Private Market, “Secondary Scene 2026 Outlook,” https://www.nasdaqprivatemarket.com/secondary-scene-npm-annual-private-market-report/.
20. Forge Global, “How AI Shaped the Private Market & the Data Behind 2025’s Transformation,” 2025, https://forgeglobal.com/insights/how-ai-shaped-private-market-data-behind-2025-transformation/; Nasdaq Private Market, “Secondary Scene 2026 Outlook,” https://www.nasdaqprivatemarket.com/secondary-scene-npm-annual-private-market-report/.
21. SaaStr, “OpenAI’s $6B Secondary: The Largest Employee Liquidity Event in Tech History,” https://www.saastr.com/openais-6b-secondary-the-largest-employee-liquidity-event-in-tech-history/; CNBC, “OpenAI wraps $6.6 billion share sale at $500 billion valuation,” October 2, 2025, https://www.cnbc.com/2025/10/02/openai-share-sale-500-billion-valuation.html (subscription required).
22. Forge Global, “How AI Shaped the Private Market & the Data Behind 2025’s Transformation,” 2025, https://forgeglobal.com/insights/how-ai-shaped-private-market-data-behind-2025-transformation/.
23. CNBC, “OpenAI trial recap: Musk cross-examination gets heated with Altman’s lawyer on day 3,” April 29, 2026, https://www.cnbc.com/2026/04/29/musk-altman-live-updates-day-3-open-ai-trial.html (subscription required); NextWeb, “Musk v. Altman trial begins with $150B at stake over OpenAI’s nonprofit-to-profit conversion,” https://thenextweb.com/news/musk-altman-openai-trial-credibility-nonprofit.
