Can generative AI video be used in higher ed marketing? 

Although not yet ready for prime time, generative AI video shows potential to transform recruitment, campus tours and storytelling—if humans lead the way.

By: John Azoni
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There’s plenty of hype about the future of video marketing in a world where generative AI is seemingly taking over. The idea that a marcomms professional with no video production training can type in a few-sentence prompt and, in seconds, get a polished and compelling video that’s on brand and ready for prime time is an alluring thought. And we might get there someday. But in reality, these tools are far from ready to be adopted in everyday marketing and communications content. 

At the same time, examples from major brands have shown much promise. In the following, we will unpack two examples of generative video used in the marketplace today and the limitations of current generative video tools available to the public.

Case Studies in AI Video Innovation

1. Toys “R” Us and Sora AI 

Back in February 2024, OpenAI announced the release of Sora, a groundbreaking generative AI platform designed to revolutionize video content creation. The marketing crowd went wild, but as of December 2024, Sora has not been released to the public. Toys “R” Us did get backstage access though and tapped creative agency, Native Foreign, to create a dreamy commercial telling the story of the founder of the toy chain, Charles Lazarus.

The results were impressive; however, the idea that some Toys “R” Us intern in her home office just typed in a few sentences into Sora and got this amazing commercial is extremely far-fetched. I spoke with the chief creative officer at Native Foreign, who sent me this case study unpacking the process behind its making. In short, it involved a wraparound team of artists, musicians and animators to bring this to life (translation: a lot of money). Still, it’s a great example of how generative AI can be used to aid in the process of manual content creation.

2. Carvana’s “Joyride” Campaign

To celebrate its 10th year in business, Carvana blended AI-generated art and audio with human artists and animators to create a playful and fun narrative about the car buyer’s journey. The kicker is that each video (more than 1.3 million) was personalized to each Carvana customer. In the example below, the customer bought a blue 2019 Volkswagen Beetle on April 29, 2020, in Long Beach, CA. Based on these variables and others, the voiceover would change to make references to those unique identifiers, like referencing how everyone was making sourdough bread in 2020.

For higher ed marketers, these examples underscore a critical point: while current tools may have limitations, the potential applications, like personalized recruitment videos, interactive campus experiences and student/alumni storytelling, are boundless as the technology matures.

The Tools Available for Generative Video

When it comes to actually making something like what we see above, the tools available to the public are ones like RunwayML, Synthesia, Pictory, DeepBrain AI, Kaiber and Colossyan Creator, with the mainstream tool being RunwayML.
As a higher ed video creator working in a documentary style, there are extremely few times when my team would have a legitimate use for an AI-generated video clip. Even if we could get the process to work how we wanted, those clips would still look too jarring next to real footage our cameras produced. 

A Practical Test with Generative Video Tools

We encountered a potential use case while working with a non-higher ed client, an anti-human-trafficking organization for whom we produce survivor stories annually for their year-end campaign. Survivors often lack documentation of their darkest moments, requiring creative b-roll for retelling their stories.

In one case, a survivor, recounting her abuse as a child said something along the lines of “people kept coming into my room at night.” We thought this would be an appropriate use for an AI-generated series of b-roll clips because the moment was a memory from the past, and a dark one at that, which lends itself to being a little abstract and cryptic.
Utilizing RunwayML we tried again and again with various prompts and source material for reference to develop even one usable b-roll clip. After about an hour, we gave up and went a different route. The clips the program returned were not accurate to what we were asking, and the visuals kept morphing and doing unnatural things as the shot progressed, which is extremely common with the current state of generative video capabilities.
To get anything usable we would have had to approach it like Toys “R” Us and Carvana did by bringing in artists and animators to create visual assets from scratch to pair with the AI-generated ones. In that scenario, it would be faster and way more cost-effective to just hire actors and shoot the scene we wanted in a live-action format. 

Possibilities for the Future

Although today’s tools have some constraints, the generative AI video landscape is advancing quickly. For higher education, the future might include at least three applications.

  • Personalized Recruitment Videos: AI could generate tailored videos based on a student’s interests, showcasing specific programs, faculty or extracurriculars.
  • Immersive Campus Tours: Imagine AI-driven virtual tours that adapt in real time based on user interactions, creating a highly engaging experience.
  • Supplemental Visuals: The ability, for example, to input employment data into an AI tool and have it return a customized animated graph showing the rise of demand for a particular field of study. It could also bring still images to life in a believable way. 

In these scenarios, humans are still an essential part of the equation. I don’t see a reality anytime soon in which higher ed institutions can replace creative job roles like videography, graphic design or web design completely with AI. Even if the visuals could be automated, you’d still need someone behind the wheel to control the prompts and manipulate the results.

Charting a Path Forward

The potential of generative AI in higher education isn’t just about replacing traditional methods—it’s about enhancing what’s possible. By experimenting with available tools, marketers can integrate AI into their workflows in low-risk ways, such as social media content or internal communications. Meanwhile, keeping an eye on emerging innovations will prepare institutions to scale their video strategies as the technology matures.

Generative AI video is on the brink of becoming an indispensable tool for higher ed marketing. As these tools evolve, so will their ability to help colleges and universities create deeply engaging, emotionally resonant content at scale. For now, the key is to lean into experimentation, embrace the possibilities, and remain focused on the storytelling that will always form the heart of effective communication.

John Azoni

John Azoni

Contributor

John Azoni is a content creator and seasoned video producer channeling his many years of production and content marketing learnings into higher education. He is the Founder and Executive Producer at Unveild, a video production company helping colleges and universities tell engaging human-centered stories.

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Can generative AI video be used in higher ed marketing? article image. Split image: On the left, a close-up of hands typing on a keyboard, overlaid with lines of programming code. On the right, three diverse students sitting together in a library, engaged in collaborative learning, with an overlay resembling a video timeline below.

Can generative AI video be used in higher ed marketing? 

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