Research and development can easily become a series of disconnected experiments. Try a new tool. Generate something interesting. Learn a few things. Move on.
That’s never been how I approach it.
When I explore a new technology or creative approach, I want the work to have a potential destination. It might become something we can use internally, something we can share with clients, or the foundation for a larger idea or workflow.
The experiment doesn’t always need to succeed. That’s part of R&D. But I believe it should begin with the possibility of becoming something useful.
Instead of asking only, “What can this tool do?” I prefer to ask, “What could this help us communicate, create, or improve?”
Research with a destination
For me, R&D isn’t separate from work. It’s just one way of pushing it forward.
Even when testing a new platform, technique, or AI model, I try to give the work a practical direction. That might mean developing a new visual treatment, finding a more efficient way to produce assets, or exploring an idea that could eventually become client-facing.
That still leaves plenty of room for experimentation. I can fail, change directions, and discover unexpected avenues I hadn’t thought of. The difference is that the work begins with intent. I want to learn by making something that has the potential to matter.
Finding the story inside the exploration
For this particular experiment, I was testing several new AI models. I wanted to push some boundaries and see what they could do beyond the usual “stock video” approach we’d already explored and established standards for. The next step was finding the story to tell.
Data migration is a good example. It’s important, complex, and often business-critical, but it’s not naturally cinematic. We’d previously discussed creating a video about the subject, but the idea was put on hold. I decided to build my experiment around it and see if I could create something compelling and potentially usable.
The obvious visual approach might normally involve servers, cloud icons, animated data streams, or people staring at dashboards. Those images can explain the subject, but they don’t necessarily make someone want to keep watching and they’re overdone. I wanted to approach it from a completely different direction.
So, I started looking at data migration from a different angle. What does it actually represent? Movement. Risk. Transition. Leaving one environment behind and moving toward another. Carrying something valuable through uncertainty and making sure it arrives intact.
That creates a much more human and visual foundation for storytelling, one built around real stakes the audience can actually feel.
Thinking outside the “tried and true” doesn’t mean making the subject unrecognizable. It means finding a metaphor or point of view that allows the audience to experience the idea instead of simply being shown a diagram of it.
I asked myself, “What metaphor could carry all of that?” I bounced around a few ideas before landing on a cattle drive. With the recent popularity of Neo-Western television and film, the visual language felt both familiar and timely. It represented the movement, danger, responsibility, and scale I wanted the story to communicate.
Because the experiment began as a way to push new AI video models in a different direction, I also decided to present the story as an animated Western-inspired oil painting. Something you might see in an old hunting lodge.
I now had the concept and visual direction: data migration as a cattle drive across the American West, in an animated Western-inspired oil painting. Data becomes the herd, something large and valuable that must be kept together and moved safely. The lead is responsible for navigating the route, anticipating danger, and making sure everything arrives where it needs to go.
Using AI to bring the story to life
AI made it possible to explore this idea visually, without the cost and complexity of producing it traditionally. It helped me polish my script, create quick storyboards and concept art, and generate the assets I needed to turn it all into a final video.
But AI was not the idea.
The idea was to make data migration feel like a consequential journey. AI was a production tool that allowed me to build that world.
That distinction matters. Without a clear story, the finished piece could easily have become just a collection of impressive Western imagery. Each shot needed to advance the journey. The landscape had to become more threatening. The route had to narrow. The person leading the herd had to feel responsible for its progress. The eventual arrival in open country had to feel earned. And the narration had to match up.
The visuals also needed to connect back to a real business message: AI readiness does not begin with AI. It begins with the data foundation underneath it.
That is where I believe AI storytelling becomes most interesting. It gives us the ability to visualize ideas that might previously have been too abstract, expensive, or unconventional to produce. But technology can’t replace the need for a compelling concept, thoughtful pacing, or a reason for the audience to care.
Story still comes first.
The finished video became more than a test of AI-generated filmmaking. It became an example of how a familiar technical topic can be reframed into something unexpected, visual, and human. That is ultimately what I want from research and development: to explore new tools with a real destination in mind, find a story worth telling, and use the technology to bring that story to life.
See more of our work on our YouTube channel or on our AI videos page!