When AI Helps Create, Who Owns the Upside?

When AI Helps Create, Who Owns the Upside?

A line that’s about to get very blurry

There’s growing discussion around a provocative idea reportedly being explored by OpenAI:

If you build something valuable with ChatGPT—an app, a tool, even a scientific breakthrough—the AI provider could eventually claim a share of the revenue.

Not instead of subscription fees.

On top of them.

Even if:

• You already pay for access

• The idea was entirely yours

• The AI never touched production code

That’s a fundamental shift in how tools, ownership, and value creation have worked for decades.

The traditional rule: you pay for tools, you own the output

Historically, the logic was simple:

• Buy a guitar → the manufacturer doesn’t own your hit song

• Write a book in Microsoft Word → Microsoft doesn’t get royalties

• Design in Adobe → Adobe doesn’t claim IP

You paid for the tool.

The output belonged to you.

This principle underpins modern entrepreneurship, IP law, and innovation itself.

Why AI complicates everything

AI isn’t just a passive instrument.

It can:

• Suggest architectures

• Generate code

• Refine business logic

• Explore research paths

That makes it feel less like a hammer—and more like a collaborator.

Supporters of revenue sharing argue:

• If AI meaningfully accelerates or enables value, shared upside is fair

• AI models are expensive to build and maintain

• This aligns incentives between creators and platforms

On paper, it sounds reasonable.

In practice, it’s explosive.

Where does “instrumental” end?

This is the real danger.

If revenue sharing becomes normal:

• Does your coding assistant own part of your startup?

• Does an AI that helped brainstorm naming rights get equity?

• Does summarizing research papers create downstream claims?

Most modern work involves AI somewhere in the process.

If contribution equals ownership, nearly everything becomes encumbered.

Why SMBs, healthcare, law firms, and schools should care

This isn’t a solo-founder problem—it’s an enterprise risk issue.

• SMBs: Who owns internally developed tools built with AI assistance?

• Healthcare: Does AI-assisted research introduce ownership disputes?

• Law firms: Client IP and privilege become harder to define

• Schools: Student-created work raises new rights questions

Unclear ownership isn’t theoretical—it’s legal exposure.

The slippery slope problem

Once revenue sharing exists:

• Subscription pricing no longer defines cost

• Long-term upside becomes unknowable

• Risk moves from predictable fees to contingent claims

That uncertainty chills innovation fast.

Tools should empower creators—not shadow them indefinitely.

The core question

AI absolutely changes how we create.

But changing how we create doesn’t automatically justify changing who owns the result.

If paying customers no longer fully own what they build, AI stops being a tool—and starts acting like a silent partner.

And silent partners are the most dangerous ones.

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