The productivity myth dissolves
72% of uploaders (surveyed video posters aged 14 to 44) say they use AI on videos or images, according to YouTube's Culture & Trends team research of major generative video trends and surveys with NRG asking thousands of people about their interests and attitudes toward generative AI. That figure alone suggests generative video is past experimental. What matters is what people are doing with it.
Rather than using it strictly for utility, people use it to insert themselves into content and play at being the director of their own lives. More than two-thirds of people who post AI videos say they have featured themselves in their content.
The insight here is straightforward: when the barrier to video creation drops, the first instinct isn't to automate away the self. It's to put the self front and centre in contexts that were previously out of reach. That changes what generative AI is for, and where social marketers should look when they think about what this technology unlocks.
Emotional storytelling before efficiency
Many popular trends enable uploaders to weave AI imagery into a visual record of their personal identity exploration. By using it to visualize their complex emotions, people turn knotty feelings into cathartic imagery that others can empathize with.
The "hug your younger self" trend is the clearest example. In these videos, people animate and interact with childhood photos to express emotions that are difficult to put into words. Through comments and video responses, these videos became a social experience that evoked nostalgia and an emotional rapport with other participants.
61% of surveyed video posters in the past year agree that they're interested in using AI to insert themselves into content.
This isn't about making production faster. It's about making emotional states visible and shareable in ways static photos or text never could. For brands trying to understand where generative video fits into content strategy, the answer isn't efficiency tooling. It's giving audiences new ways to express what they already feel.
By using it to visualize their complex emotions, people turn knotty feelings into cathartic imagery that others can empathize with.
YouTube Culture & Trends reportPassion projects without production constraints
Hobbyists are removing the constraints of reality and discovering fresh approaches to personal passions. Prospective fashion designers turn flat sketches into photoreal runway looks, while fans visualize themselves in tactile cosplay or generate novel fan fiction.
The pattern holds across niches. Someone sketching a jacket on paper can now see it worn on a model under studio lighting. A cosplayer imagining a crossover between two franchises can render themselves in both costumes, styled and lit as if from an official photoshoot. A Minecraft fan can place themselves inside ASMR mukbang videos set in fictional game environments.
What links these use cases isn't the category. It's the removal of technical and logistical barriers that previously sat between an idea and its expression. You no longer need a sewing machine, a photographer, a costume budget, or even a clear idea of how to execute the thing you're imagining. The generative tool fills the production gap, and the creator supplies the concept and the context.
For social media marketers, this matters because it reframes where community happens. Passion-based content no longer requires expert skill or access. It requires passion and a prompt. That lowers the floor for participation and raises the volume of niche content worth tracking.
What this means for brand strategy
The YouTube findings suggest three implications for anyone building content or running campaigns on platforms where generative video is now accessible.
First, the shift from efficiency to identity changes what creators want from tools. Brands offering generative features need to design for self-expression, not time saved. If the pitch is "make content faster," it misses the motivation. The real pull is "put yourself in contexts you couldn't reach before."
Second, emotional and passion-driven content is now structurally easier to make, which means more of it will exist. Marketers tracking trends or planning influencer partnerships should expect a higher baseline of hobbyist content in niche categories. The quality bar for produced content rises when someone with no budget can render a polished concept in minutes.
Third, the communities forming around these tools are using them for self-exploration, not just output. That's a different engagement model. It's less about subscribing to a creator for their expertise and more about participating in a shared format or trend where everyone's testing their own version. Brands that understand that distinction can build campaigns around participation rather than reach.
YouTube has built generative video directly into Shorts through its Veo-powered Dream Screen tool, which now lets creators generate six-second standalone clips from text prompts. That infrastructure is live, not speculative. The behaviour the Culture & Trends report documents is happening at scale right now, and the people doing it aren't waiting for brands to catch up.
The gap between scepticism and adoption
Despite popular skepticism of the role generative tools are playing in video creation, using this technology in content creation is already surprisingly common. That disconnect between perception and practice is worth noting.
Public conversation around generative AI still tilts toward concerns about authenticity, labour displacement, and low-quality spam. Those are real issues, and platforms including YouTube have updated policies to address inauthentic mass-produced content. But the report shows a parallel reality: millions of people are using generative tools not to fake something, but to show something real about themselves that they couldn't otherwise visualise.
The scepticism hasn't stopped adoption. It's shaped how people use the tools. The dominant mode isn't faceless automation. It's personal, emotionally legible content where the creator's identity is the point.
For marketers, that matters because it suggests the audience isn't rejecting AI-assisted content. They're rejecting content where AI replaces the human, not content where AI helps the human say something they couldn't say before. The distinction is sharp, and campaigns that ignore it will read as tone-deaf.
The intersection with platform infrastructure
YouTube's generative tools are embedded where creators already work. Dream Screen sits inside the Shorts camera. AI-generated backgrounds and standalone clips don't require third-party apps or exports. That integration shapes adoption in ways standalone tools can't match.
When generative features live inside the creation flow, they become part of how people think, not something they bolt on after. The report's findings reflect that. People aren't treating AI video as a separate category. They're treating it as another option in the same menu as filters, effects, and editing tools.
That has competitive implications. Platforms that embed generative video natively will capture more personal, identity-driven content than those that rely on users importing AI-generated assets from elsewhere. Instagram's teleprompter feature changed how creators script Reels by putting the tool inside the camera. Generative video will follow the same path.
Brands running YouTube Demand Gen campaigns or building creator partnerships should expect this shift to accelerate. The content landscape in six months will include significantly more AI-assisted personal and hobbyist video than it does today, and the quality and emotional resonance of that content will be higher than most marketers currently assume.
What to watch next
The YouTube Culture & Trends report captures a moment, not an endpoint. The behaviours it documents will compound as the tools improve and as more platforms follow YouTube's lead.
Three signals to track: how quickly other platforms integrate generative video into native creation tools, whether the emotional and passion-driven use cases expand beyond early adopters into mainstream behaviour, and whether brands start designing campaigns that invite participation in generative formats rather than simply observing them.
The shift from utility to identity isn't a niche trend. It's a structural change in what people want from creation tools and what they're willing to share. Social media marketers who treat generative video as a productivity play will miss the real opportunity, which is helping audiences put themselves into content they couldn't make before.
The hobbyists and emotional storytellers are already there. The question is whether brands can build for that reality, or whether they'll keep pitching efficiency to people who never wanted to save time in the first place.