The Next Frontier in AI Video: Rights as Infrastructure

For years, generative AI felt like the Wild West. A blur of innovation, imitation, and intellectual chaos. The logic was simple: scrape the internet, feed the model, and let creativity emerge. But now, as AI video systems mature, something more fundamental is taking shape: the emergence of rights management as core infrastructure.

The moment was inevitable. Every new technology starts with an explosion of openness and then, over time, settles into structure. The early internet had Napster; streaming brought licensing. Social media had reposts; now it has rights attribution and watermarking. In AI, that same inflection point just arrived.

OpenAI’s Sora 2 and Meta’s Vibes both signal that rights, not just compute, are becoming the defining constraint and competitive edge in generative media.

From “Opt-Out” to “Opt-In”: OpenAI’s Course Correction

When OpenAI launched its first wave of image and video tools, the underlying assumption was that everything online was fair game unless someone said otherwise. That “opt-out” approach created breathtaking capabilities and massive backlash.

With Sora 2, OpenAI has flipped the model. Instead of treating content as a default input, it now requires explicit, opt-in permission from rights holders — and for the first time, introduces revenue sharing with those who license their IP.

It’s a philosophical and practical shift: from “train now, apologize later” to “license before you train.”Even the outputs reflect this maturity. Each Sora 2 video now carries embedded watermarks and usage rights, a small but significant reminder that ownership in AI is no longer invisible. It’s machine-readable, traceable, and monetizable.

Meta’s Vibes: Creativity Without Clarity

Meta’s new experiment, Vibes, takes the opposite approach. It leans into remix culture — encouraging creators to generate, edit, and reimagine clips freely across Instagram and Facebook.

It’s fun, fast, and viral but legally vague. Any AI-generated clip gives Meta sweeping usage rights, while third-party content holders receive no formal attribution or payout. Creativity scales, but compliance lags.

It’s a reminder that AI-native media needs more than tools for creation. It needs systems for ownership.

TikTok: Rights in Motion

TikTok may be the quiet leader here. The platform already labels AI-generated videos (“AIGC”) and has partnered with the Content Authenticity Initiative (CAI) and C2PA to embed provenance data directly into media files.

It’s not perfect, fully synthetic clips are still excluded from monetization but the foundation is solid: authenticity, traceability, and payouts.Among the major players, TikTok has been the first to make AI rights both visible and enforceable.

The Shift No One Can Ignore

Sora’s opt-in system is more than a product update. It’s a signal: rights management isn’t just a compliance checkbox; it’s becoming the new distribution layer.

We’re watching a full-stack inversion play out in real time.AI companies once obsessed with compute and scale are now confronting what media owners have known for a century:  that data without rights is liability.

Or put differently:

The next generation of AI isn’t built on more data. It’s built on better permission.

Why It Matters for Everyone Building the Future

This is the long-awaited convergence of AI and media economics. For decades, creators and studios treated their archives as libraries, valuable, but static. Now those same libraries are becoming training capital, assets that can be securely licensed into AI systems while maintaining ownership, provenance, and recurring value.

That’s not just a legal innovation; it’s a business model shift. Rights management, watermarking, and licensed training are not just safeguards, they are revenue engines.

The Clairva View

At Clairva, this moment feels familiar. Our thesis has always been simple: the most valuable datasets in the world are the ones you can trust.

We have built the infrastructure that turns video IP into structured, rights-managed, AI-ready datasets, starting in the Global South, where rich cultural data is often underrepresented but incredibly valuable.

As OpenAI, Meta, and others move toward rights-based models, one truth is becoming impossible to ignore:

The future of AI video will be defined not by who has the most content, but by who has permission to use it.

This is not the end of the Wild West. It’s the beginning of the build-out, where provenance, licensing, and fairness are not friction. They are the foundation.