Behind the Sora Shutdown
In March 2026, OpenAI shut down Sora — the standalone app, the API, and the ChatGPT video features all went dark. A product that hit a million downloads in five days, that generated more buzz than ChatGPT at its peak, just gone.
The reasons aren’t complicated: compute costs were unsustainable, monetization never found solid ground, and Disney’s $1 billion investment deal fell through.
But here’s the interesting part. After Sora’s exit, the AI video market actually got more active. Domestic Chinese tools exploded. Runway kept pushing in the professional space. Google quietly upgraded Veo to its third generation. Instead of cooling off, the industry shifted from an “arms race” to a “practical tools” phase.
Who’s Actually Making Videos in 2026
Let’s run through the players worth knowing.
Kling AI (Kuaishou): Currently the top domestic option. Generates up to 3 minutes of 1080p video. Solid physics simulation and multi-shot narrative features. The most practical feature is multilingual lip sync — Mandarin, Cantonese, Sichuanese — all supported.
seedance2.0 (ByteDance): Deeply integrated with CapCut’s ecosystem. Strong Chinese language understanding, low barrier to entry. If you’re a Douyin/TikTok creator, the pipeline from seedance2.0 to CapCut is the smoothest option available.
Runway Gen-4: The choice for professionals. Supports 4K output, integrates over 30 AI tools. If you care about visual quality, the $12-76/month subscription is worth it. Hollywood teams are already using it for pre-visualization — cutting what used to take two weeks down to three days.
Google Veo 3: This is the quality ceiling. Cinema-grade output with spatial audio. Best suited for brand campaigns where production value matters most.
There’s also an interesting open-source option — Alibaba’s HappyHorse-1.0 (the open-source version of Tongyi Wanxiang). 15 billion parameters, Apache 2.0 license, free for commercial use. Runs on consumer GPUs. You only get 10 seconds of 1080p, but for small teams, that’s enough to start.
From “A Fortune” to “A Day’s Budget”
In 2024, making a decent AI video was still expensive. Not anymore.
A full manual AI video workflow — ChatGPT + Midjourney + Runway + ElevenLabs + CapCut — runs about $88-130 per month. All-in-one platforms like Virvid charge $19/month for 30 short videos.
Compare that to traditional production: a 30-second ad spot, from concept to final cut, takes at least a week and costs tens of thousands. With AI, two hours gets it done for under a tenth of the cost.
This is why ad agencies, educators, and e-commerce teams are all moving in this direction. Not because they’re visionaries — because the math is so obviously in their favor.
More Tools, But What Actually Matters
AI video tools in 2026 show three clear trends:
Agent-driven workflows: Tools are starting to accept natural language instructions for end-to-end processes. You don’t need to learn complex parameter panels — just describe what you want.
Multimodal integration: Text, images, video, and audio flow through the same pipeline without format gymnastics.
Fine-grained control: Alibaba’s Tongyi Wanxiang 2.2 uses a MoE architecture supporting 60+ parameters for lighting, composition, and color. AI video is moving from “can it generate” to “can I control every detail.”
But here’s the thing I keep coming back to: tools are tools. I’ve seen people spend hours perfecting prompts only to produce content nobody watches. AI solves the “can I make this” problem. It doesn’t solve “will anyone care.”
It’s Not Perfect, But It’s Getting There
Let’s be honest — AI video still has problems.
Physics remains a weak spot. Water flow, fabric movement, subtle lighting changes — models still stumble. In longer clips, character movements can feel off. You can still see the seams if you look closely.
Compute costs have come way down, but high-res generation still needs serious hardware.
Then again, these problems are signs of a maturing industry. Two years ago, generating a few seconds of blurry footage was exciting. Now the conversation has shifted from “can it generate” to “how do we make it better.” That shift alone is progress.
What This Means for Regular People
I keep asking myself: when AI video is everywhere, who actually benefits?
Big studios and ad agencies, obviously — they’ll produce more content for less money. But I think the real wildcard is independent creators.
A 22-year-old marketing specialist in New York, couldn’t sleep one night, opened Google Veo on a whim, typed “night vision footage of rabbits bouncing on a trampoline in the backyard, then one disappears,” and posted it to TikTok. Millions of views in days. Not a marketing campaign — just a bored person messing around.
A writer fed their essay into an AI tool and found it could understand the emotional tone of their words — slow, lingering visuals for contemplative passages, clean and direct imagery for analytical sections. The pacing was better than what their editor friend could do.
AI is flattening the “can I film this” barrier. All you need is something worth making.
Wrapping Up
Nobody knows exactly where this goes. But a few things seem clear:
AI video tools will get cheaper and easier, eventually becoming as mundane as photo filters.
Small teams focused on specific niches will have an edge over big ones, because they’re closer to real use cases.
Copyright and ethics questions are going to get louder — who owns generated video, does using someone’s style count as infringement — and the law is nowhere close to answering them.
For anyone who’s been thinking about making video but found it too hard: 2026 is the year that excuse stops working. The tools are good enough, and the barrier has never been lower.
📖 Recommended Reading
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