Cut To The Web
Why generative video is more than content, it’s the next interface of the internet.
For years, the internet was a place you scrolled. Soon, it’ll be a place that moves.
Video generation, once the final frontier of generative AI is cracking open. Google’s Veo, OpenAI’s Sora, Runway, Pika, Kling, Hedra, Vidu: the roster’s growing fast. But this isn’t just about a new content format. It’s about a shift in medium and control. The web as we know it is built around text and images. But that stack’s starting to look stale. What happens when every interaction is animated, personalized, and performed?
We’re about to find out.
The Next Level of Generative AI
It’s not just about generating pixels. It’s about simulating motion, physics, lighting, continuity, perspective, and time. Static image generation asks a model to understand a single frozen moment. Video demands that it understand how moments evolve. It has to track multiple entities, preserve identities across frames, model consistent lighting and shadows, and infer what happens next based on what’s already happened.
Those challenges made video the final boss of generative media. The computational complexity is orders of magnitude higher than text or image generation. Models need larger context windows across frames, better temporal coherence, and more training data that captures not just what the world looks like but how it behaves. For years, that complexity made video feel out of reach.
Now, models like Sora and Veo can generate minute-long, photorealistic clips that don’t just look good, they move right (mostly). Sora uses transformer-based architectures trained across both image and video data to render scenes with complex interactions, weather systems, camera pans, and implied emotion. Veo, Google DeepMind’s contender, leans into compositional control, letting users specify shots, actions, and styles with far more precision.
Meanwhile, Runway and Pika are playing a different game. Rather than chasing film-grade realism, they’re optimizing for speed, and creative flexibility. Runway’s Gen-2 lets creators iterate quickly, remix styles, and even animate still images or storyboards into stylized video. Pika, on the other hand, is designing for the TikTok generation with quirky, fun-to-share outputs, fast rendering, and native hooks for social media workflows.
In China, the pace is accelerating even faster. Kling and Moonvalley have burst onto the scene with shockingly fluid short videos, often beating Western demos on movement quality and camera realism. But what’s more important than the output is the deployment strategy. These models aren’t being rolled out as standalone tools, they’re being embedded directly into existing platforms like Douyin, Xiaohongshu, and Bilibili. In other words: fully integrated, not opt-in.
What unites all of these companies isn’t just that they can generate video. It’s that they’re each betting on different futures for what video is. For OpenAI, it’s a new language model, one that communicates in motion. For Google, it’s a way to deepen the YouTube ecosystem and unlock more sophisticated creative tools. For Runway and Pika, it’s about democratizing production and building for internet-native formats. And for the Chinese platforms, it’s about vertical integration and owning the full stack.
Videos Through the Stack
The market for generative video isn’t theoretical it’s already in motion, and it's bigger than most people think. Let’s look through the major sectors impacted.
Marketing
Starting with perhaps the most obvious: marketing. Brands are already using AI-generated video to produce personalized campaigns at scale. Dozens, sometimes hundreds of variations of the same core ad, tailored by region, age group, interest segment, or even individual browsing behavior. The promise here isn’t just speed or cost, it’s hyper-specificity. Marketers can swap out backgrounds, characters, languages, or voiceovers with just a new prompt. Basically cutting out actors, production and studios.
And the opportunity is massive. According to Statista, the global digital advertising market is projected to hit $740 billion by 2028, with video ads making up the fastest-growing segment. AI-powered video production sits at the intersection of this trend, unlocking dynamic ad generation for platforms like YouTube, Instagram, TikTok, and even CTV (connected TV). In a world where attention spans are short and creative fatigue is real, AI gives brands the ability to A/B test visual storytelling at the speed of a browser refresh.
It also shifts the economics. Traditional ad production costs can range from $5,000 to $100,000+ for a 30-second spot. AI tools cut that down by an order of magnitude, while enabling far more experimentation. Instead of producing one big-budget hero video, brands can generate micro-campaigns designed for niche audiences and track which narratives actually convert.
Film and Entertainment
While the major studios are still watching from a distance, independent creators are already building short films with nothing but prompts. Music videos, concept trailers, experimental cinema, AI video lowers the barrier to entry so much that production becomes a solo act. In the next five years, it’s entirely possible we’ll see the first Sundance short that was 90% model-rendered, and it won’t look like a gimmick.
Education
In education, generative video could becomes an on-demand tutor. Students ask questions and receive not just an answer, but a visual walkthrough (a diagram that comes alive, a science concept illustrated in 3D, a historical moment reenacted). AI Video becomes not just illustrative, but interactive.
Enterprise
Even in enterprise workflows, use cases are emerging: onboarding videos customized per role, internal comms rendered as visual updates, or training modules generated in minutes instead of weeks. Combine that with agentic systems and you’re looking at the beginning of real-time, conversational UI delivered through motion.
The result is a new market category that sits somewhere between creative tooling, content automation, and interface design. Right now, most companies are focused on entertainment, creators, and marketing. But that’s just the entry point.
The Business Model
Some are leaning into SaaS and subscriptions (Runway, Pika) targeting creators, marketers, and small studios with intuitive tools and community-driven growth. Others are betting on API-first distribution (Sora) to be embedded within enterprise workflows and developer stacks. Then there’s Google’s Veo 3, which sits somewhere in between. With its native ties to YouTube and the Google Cloud ecosystem, Veo is less about individual users and more about platform leverage. It could become the rendering engine for Google’s internal video products, or a turnkey solution for enterprise video generation across retail, education, and advertising.
For U.S. brands, this presents a new kind of competitive terrain. They’re no longer choosing between agency vs. in-house. Now it’s studio vs. synthetic. Nike, Coca-Cola, and Sephora have already started experimenting with AI-generated video in campaigns. And as tools become more controllable and more brand-safe, it’s only a matter of time before Fortune 500s make AI their default creative director.
It’s still too early to call the winner. But one thing’s certain, this isn’t a niche toolset. It’s a new economic layer.
From Content to Interface
What makes this wave different is that it’s not just about what we create, it’s about how we experience information.
Generative video doesn’t just replace static content. It replaces static interaction. Imagine an AI agent that explains your question not with a paragraph, but with a skit. A product that doesn’t just show a picture, but generates a demo that adapts to your preferences. A website that doesn't load pages, but generates a 15-second trailer based on what you're trying to do.
The line between interface and content starts to blur, and in that blur, a new kind of internet starts to take shape, one that performs and adapts in motion. Zoom out, and the stakes get clearer. This is about more than just better trailers or AI music videos.
We’re watching video evolve from a medium into an infrastructure layer. That shift brings with it a new set of winners and losers. Who gets to decide how dynamic the web becomes? And what does that mean for traditional software UX, for education, for commerce, for communication?
My Take
Everyone’s chasing better video quality. I think the key is chasing better video interfaces.
Models like Sora and Veo are impressive. But the real unlock won’t be the prettiest scene, it’ll be the most native interaction. The moment when video becomes not just content, but the operating system of the web. When agents start responding with motion and websites stop loading and start performing. I think once users expect movement, a static web won’t cut it.