In the ongoing exploration of sustainable profit paths, OpenAI is酝酿 a more disruptive business model: taking a share from "AI-Aided Discoveries" achieved by customers using its AI systems. According to insiders, this plan is still under internal discussion but has already attracted widespread attention in high-value R&D fields such as technology, pharmaceuticals, and materials science.

What are "AI-Aided Discoveries"? They refer to innovative outputs accelerated by enterprises or research institutions using OpenAI's large models (such as GPT, Operator agents, etc.)—for example:

- New candidate drug molecules identified by pharmaceutical companies through AI;

- New alloy formulas discovered by material laboratories;

- Optimized circuit architectures developed by chip design teams;

- Even new products incubated by startups based on AI-generated ideas.

OpenAI envisions that if these results achieve commercialization (such as drug launches, patent licensing, product sales), the company would collect a "technology empowerment fee" at a certain percentage. This differs from traditional API usage billing, as it upgrades the charging model from "usage volume" to "value creation," aiming to deeply bind AI with customer success.

If implemented, this move would completely change the relationship between AI service providers and their clients: OpenAI would no longer be just a tool provider, but a **co-sharer in the innovation value chain**. Supporters argue that this could incentivize AI companies to continue investing in high-difficulty basic research; however, critics worry it may lead to disputes over intellectual property ownership and increase the legal and financial complexity for businesses using AI.

Currently, OpenAI has not disclosed specific sharing ratios, applicable scope, or implementation mechanisms. However, considering its annualized revenue reached over $20 billion in 2025, this move may aim to further open up the ceiling of high-value B2B markets—especially in research, biopharmaceuticals, and other fields characterized by "high returns and long cycles."

Notably, similar models already exist in the cloud computing and EDA (Electronic Design Automation) industries, but incorporating AI large models into a "results-sharing" framework is a first. Once implemented, it could reshape the entire AI industry's business logic: **Future AI competition is not only about technology, but also about the struggle for ecosystem sharing rights and innovation influence**.

Between its AGI vision and practical profitability, OpenAI is taking a bold step—but this path is destined to face three major challenges: legal, ethical, and commercial ones.