As a creative collaborator at a Warsaw-based video production company and a Gen AI nerd, I've spent the past year toying around with video generation tools—from Sora to Runway and, more recently, Veo-3.
As you can guess, my life has been a whirlwind of prompts, pixels, and generative pandemonium.
Anyone who’s spent any time online has surely seen the hype: "Create a Hollywood-level commercial for $5!" or "Fire your video team, AI is here!"
It’s a compelling narrative, but as someone deep in the trenches creating AI-driven ads for actual, paying clients, I’m here to tell you the reality is a lot more nuanced, a bit messier, and infinitely more intriguing.
The truth is, commercial-ready AI video tools are absolutely here. They can slash production costs, deliver stunning visuals, and open up creative avenues we could only dream of a few years ago. But—and this is a big BUT—they are not magic wands.
Using Gen AI video platforms effectively is more like conducting a very strange, very technical orchestra than it is about pushing a button. Understanding how to amplify the power of AI with a solid foundation of traditional, human-led creative strategy is just as important as knowing which AI to use.
The Great AI Gold Rush: Hype vs. Reality in Video Marketing
Let's start with the numbers, because they're pretty wild.
Video is already king in marketing—in 2025, a staggering
Now, inject generative AI into that equation. Suddenly, the barriers to entry—cost and time—seem to be evaporating. When used cleverly, AI
But here's where the hype train can go off the rails.
Many marketers are diving in, with over half expecting AI-generated content to outperform human-made content. Yet, many quickly discover that the shiny "text-to-video" demo doesn't quite translate to a commercial that actually sells a product.
The output often looks… well, AI-generated. Characters have inconsistent faces, the lighting is just a little bit off, and the whole thing lacks a soul. This is the gap where professional experience becomes not just valuable but essential.
Pre-Production: The Most Important Part of Creating an AI Video Has Nothing to Do with Artificial Intelligence
This may seem counterintuitive, but the success of an AI-generated ad is almost completely determined before you write a single prompt.
You can't just tell an AI, "Make me a cool ad for yogurt," and expect a masterpiece. You have to do the human work first. This is where I spend the majority of my time on any given project.
Suppose you generate AI videos for a living.
A client—say, a dairy company—approaches you to promote their new sugar-free yogurt. They want a 30-second ad that feels fresh, healthy, and premium.
My process starts with a deep dive into creative strategy.
What's the core message? Who is the target audience? What feeling do we want to evoke? I brainstorm several concepts.
Maybe one concept is a bright, sun-drenched kitchen scene. Another could be a more abstract, artistic take with flowing milk and fresh fruit. If your client is brave enough, you could take it a step further by creating a cyberpunk fantasy complete with robot cows and acid milk—and introducing the promoted 100% natural yogurt as a welcome alternative to artificial, chemically altered dairy.
I tend to write a script for each promising concept, focusing on a narrative that could potentially resonate with the client. And once they choose a creative direction, I move on to the mood board.
This is the visual North Star. I gather images that define the lighting (soft morning light), the color palette (clean whites, vibrant berry tones), and the overall aesthetic. This isn't just for me; it's for the AI.
Next, I create a frame-by-frame storyboard. This is the blueprint for the entire ad. But for AI, I go one step further: generating keyframes. These are high-quality, static images for the most crucial moments in the ad, created with tools like Midjourney. I perfect the look of the yogurt cup, the texture of the fruit, the expression on a person's face. This painstaking process is the only way to ensure the AI maintains visual consistency. Without it, the yogurt cup might magically change its label design halfway through the ad.
The Art of Wielding Chaos: A Tale of Two Ads
Once you have a rock-solid plan, it's time to get down to actual
Case Study 1: The Yogurt Dream
For the dairy client, with the storyboard and keyframes in hand, I turn to models like Runway and Veo-3. The process is iterative. I don’t just generate a 30-second clip. I generate dozens of short, 3-5 second clips for each shot in the storyboard. For a shot of a spoon dipping into the yogurt, I might run the prompt ten times, tweaking it slightly to get the perfect motion and texture.
I constantly refer back to the keyframes, using them as image prompts to guide the AI: "Animate this image of a strawberry falling into yogurt in a slow-motion, cinematic style."
I wrestle with the AI to maintain consistency.
Sometimes the lighting shifts unexpectedly. Sometimes the physics of the milk splash looks just plain wrong. It’s a constant cycle of generating, reviewing, and refining. This is the "engineering" part of prompt engineering, and it takes hours of patient, detail-oriented work. Fortunately, ChatGPT and Gemini can help alleviate some of the prompting burden, but even those know-it-alls don't always get the instructions right, let alone on the first try.
Case Study 2: How a Turquoise Banana Saved an Ad Campaign
Now for a wilder story.
I had a client in the adult eCommerce space who needed a 30-second ad for a personal wellness device. As you can imagine, generative AI models are, to put it mildly, prudish. Any prompt even hinting at the product was met with a polite but firm "I can't generate that."
This is where creative problem-solving becomes your most valuable asset. I knew I couldn't show the product. So, I decided to show its effect.
My concept was built around a universally relatable hero: an exhausted young mother juggling remote work, a crying baby, and a barking dog. Her moment of escape is in the bathroom with her new "personal assistant." But what could be used as a visual stand-in? The brainstorming session was hilarious. I finally landed on the perfect, surreal substitute: a vibrant, turquoise banana. It was funny, completely unexpected, and 100% safe for any algorithm.
The execution was a hybrid masterpiece.
I used Midjourney and Sora to generate keyframes of the hero and her absurdly colored fruit, locking in the visual style. Then, I turned to Runway to animate the scenes. The ad culminates with the hero locking the bathroom door, followed by a cartoonish, house-shaking blast of energy rippling through the home.
The final ad was witty, memorable, and navigated the AI's content filters perfectly. It showed that with a dose of human ingenuity, you can guide AI to tackle even the most sensitive briefs with style and humor.
The Final Polish: Where the Real Magic Happens
Here's the biggest secret of AI video production: the raw footage the AI spits out is almost never the final product. It's the raw clay, not the finished sculpture. This is where a background in traditional filmmaking isn't just helpful; it's a necessity.
The dozens of short clips generated for the yogurt ad have to be meticulously assembled. A skilled editor sequences them to match the storyboard's pacing and narrative flow.
Then comes color grading. Even with a super-detailed prompt, you may get AI-generated clips that have slight variations in color. A professional colorist unifies them into a cohesive, cinematic look that matches the brand's palette.
Sound design is just as important. You must include the subtle clink of the spoon, the splash of fresh fruit in the yogurt, and a licensed music track to enhance the mood. Various tools can be used for this, including Veo's built-in capabilities and dedicated sound design platforms such as ElevenLabs.
Finally, the company's logo and any on-screen text are integrated. This post-production phase can take just as long, if not longer, than the generation phase, and it’s what elevates the content from a cool tech demo to a polished, professional advertisement that builds brand trust. After all, stats show that
So, Is It Really Cheaper?
Yes, but it's not "cheap."
A traditional 30-second commercial with a live-action shoot can easily run into the tens of thousands of dollars for crew, locations, actors, and equipment. The
cost of an AI-generated video ad of similar quality, like my turquoise banana project, might range between $1,000 and $5,000. That's a massive reduction.
However, the cost doesn't disappear completely; it shifts. Instead of paying for a large film crew and physical logistics, the client is investing in highly skilled human talent: creative strategists who can develop a winning concept, prompt engineers who can translate that vision for the AI, and professional editors who can turn the raw output into a polished final product. The investment moves from hardware and location fees to brainpower and expertise. For SMBs, this is fantastic news. It means a smaller budget can now compete on a much higher level, achieving a cinematic quality that was previously out of reach.
AI Is Not a Videographer’s Replacement—It’s Their New Creative Partner
The takeaway here isn't to be skeptical of AI but to be realistic.
AI video generation isn't a replacement for creative professionals; it's an unbelievably powerful tool for creative professionals.
The technology automates the tedious, opens up new visual possibilities, and democratizes access to high-quality video. According to a
The best results, however, will always come from a hybrid approach—where a smart, experienced human is guiding the AI with a clear creative vision.