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Video now dominates social media engagement, which explains why nearly 90% of businesses use video as their marketing tool in 2025. If you’re not doing the same, it’s safe to say you’re miles behind your competition, even if your product/service is superior.
We get it though, producing continuous, high-performing video at scale requires time and a hefty budget, two things that most growing brands don’t exactly have. But that’s where AI can help you; the right tools can not only automate tedious tasks like formatting, but also churn out dozens of creative variants from a single concept. This can do two huge things for your business: reduce agency spend and let you test aggressively so you can learn fast what works best.
Here is how you can use AI to scale your ad strategy and transform it into a data-driven growth process.
Each platform rewards a different creative rhythm. Naturally, TikTok and YouTube Shorts favor short, immediate hooks, while Meta’s feeds (Instagram and Facebook) still thrive on visually consistent storytelling. As for YouTube, its pre-rolls reward longer, more contextual storytelling. If you're posting ads on all platforms, you absolutely need automation; without it, you’d need separate teams or agencies to handle all that nuance.
You can feed a single creative script into an AI platform and generate vertical, square, and horizontal versions in minutes. Captions, subtitles, even CTA copy all adjust dynamically for each format. The result? Your content fits the platform’s tone, pacing, and aspect ratio without starting from scratch.
And because AI models continuously learn from performance data, your next round of videos doesn’t just look better, it’s actually smarter, too. They can identify which hooks hold attention, which CTAs convert, and which visual cues align best with your audience segments.
Traditional creative testing often relies on instinct. You think a concept looks strong, so you push budget behind it. Sure, sometimes it works, but oftentimes it doesn't, which is not that much of a problem for big brands with big budgets (but then again, they rarely go with gut feelings; they rely on data), but it is for smaller ones. AI replaces that guesswork with volume and data.
Let’s say you start with one winning 15-second concept. AI tools can spin up twenty variants, each with different intros, background tracks, or CTA placements, and then deploy them across platforms for rapid testing. Within days, you’ll know which combination drives higher view-through or conversion rates.
This is where solutions like Lucas AI video ads can be of immense help. It allows marketers to generate hundreds of on-brand creative versions, tailor content to specific audiences, and maintain brand guidelines automatically. That kind of efficiency used to require an entire creative department; now, it’s just part of the workflow.
AI tools should be a part (or extension) of your creative process, not its replacement. So, start with modular content. Separate your core video assets—script, visuals, logo, product shots, CTAs—so AI can recombine them flexibly for different use cases. Then, you automate routine edits such as trimming, resizing, and localizing subtitles.
Next, set up structured creative testing. Instead of chasing one “perfect” ad, batch-produce a set of hypotheses. Let the data surface the winners and retire the rest quickly. Feed those insights back into your AI templates so the next generation of ads evolves with each campaign cycle.
Finally, integrate creative analytics. AI-powered dashboards now track how every frame, color, or phrase impacts engagement. That granularity will help you decide where to double down, and where to stop wasting spend.
