A Secondary Share Offering That Minted Dozens of Multimillionaires
OpenAI’s internal share tender in October 2025 marked a defining moment for employee wealth creation in the AI sector. In this secondary share offering, more than 600 current and former workers were allowed to sell part of their existing equity to outside investors, collectively unloading USD 6.6 billion (approx. RM30.4 billion) worth of stock without taking the company public. Reporting indicates that roughly 75 employees became USD 30 million (approx. RM138.0 million) “sellers,” transforming paper gains into real liquidity while OpenAI remained private. This structure let OpenAI satisfy pent‑up demand for access to scarce private AI equity and, at the same time, demonstrate the scale of value already accumulated inside its cap table. Rather than a one‑time windfall, the tender functioned as a controlled wealth distribution mechanism, signalling that high‑growth AI companies can engineer major liquidity events well before any IPO.
Inside the Tender: Liquidity Without Going Public
The October 2025 deal showcased how secondary share sales can align employee, investor, and corporate interests. Because it was a secondary transaction, no new capital flowed onto OpenAI’s balance sheet; instead, outside buyers purchased shares directly from eligible employees. OpenAI reportedly adjusted its internal rules in June 2024 so both current and former staff could participate more evenly, widening access to future tenders and easing one of the biggest bottlenecks in employee liquidity. Eligibility was still constrained: employees who joined after the launch of ChatGPT in late 2022 faced a two‑year holding period before selling, and individual sale caps limited how much equity any one person could convert to cash. Even within these limits, early equity holders may have seen grants appreciate more than 100 times, demonstrating how a structured tender can create dozens of multimillion‑dollar outcomes while keeping substantial ownership locked inside the company.
Investor Confidence and the Signalling Power of Employee Cash‑Outs
Large employee liquidity events can be misread as insiders racing for the exit, but OpenAI’s tender instead became a vote of confidence in its long‑term trajectory. Demand from investors for private AI equity was strong enough that OpenAI reportedly lifted individual sale caps during the process, a sign that buyers were eager to secure ownership even at elevated valuations. Subsequent court testimony by co‑founder Greg Brockman, indicating a personal OpenAI stake worth roughly USD 30 billion (approx. RM138.0 billion) despite no initial cash investment, underlined how much value remains concentrated in private hands. Analysts such as Gene Munster have argued that OpenAI could still evolve into a multitrillion‑dollar public company, suggesting the tender was not a peak but a checkpoint. In this light, the employee cash‑outs operate as a market signal: investors are willing to pay heavily now because they believe future upside in AI productivity and platform dominance remains substantial.
A New Template for AI Company Compensation and Retention
OpenAI’s approach to secondary sales is reshaping expectations for AI company compensation and talent strategy. By staging multiple tenders—preceded by a November 2024 employee sale and a SoftBank plan to buy USD 1.5 billion (approx. RM6.9 billion) of shares—management has treated liquidity as an ongoing program rather than a single IPO windfall. This repeatable structure helps retain critical technical talent by transforming equity promises into periodic, credible cash outcomes, while still preserving long‑term ownership incentives. Across the AI industry, the precedent is clear: top engineers, researchers, and product leaders will look not only at headline salary and option grants, but at a company’s roadmap for secondary share offerings and internal liquidity. As more private AI firms emulate this model, secondary markets could become a standard pillar of AI company compensation, blurring the traditional line between private‑company risk and public‑market rewards.