Let’s start with an unpopular opinion: Who got immediately tired of the Studio Ghibli craze? Not the films themselves; those are masterworks, unsullied by the mark of machine. We mean the flood of AI-made “Ghibli-fied” content that’s been clogging up feeds like cholesterol. Every third post is some brand’s logo or corporate mascot run through a Miyazaki filter, captioned with faux wonder and algorithm-chasing hashtags.
Open any app, scroll for 15 seconds, and odds are you’ll see at least three ads that look like they were made in the same boardroom—same font, same stock aesthetic, same suspiciously upbeat voiceover reminding you to “embrace your uniqueness” while selling you the same five things everyone else is peddling.
You’re not imagining it. Advertising is starting to feel like it was designed by a single overworked art director trapped in a loop. Or, more accurately, by a shared AI model running on too many brand accounts at once.
Vipul Kedia, COO of Affle India & Emerging Markets, doesn’t mince words: “As more marketers turn to AI tools for efficiency and scale… there’s a tendency for outputs to converge toward similar tones, formats, and even visual styles.” The root of the problem, he explains, isn’t the technology—it’s how we use it. Or rather, how lazily we use it.
The average marketer today has access to a buffet of AI tools trained on the same data, responding to the same kinds of prompts, and optimized for the same KPIs. The result? Ads that feel like they were generated from the same starter pack: “Insert brand USP here, overlay with vague empowerment, finish with shiny CTA.” You get scale, sure. But you also get the sameness.
This convergence isn’t just theoretical. Data from the ANA (Association of National Advertisers) suggests that over 77% of marketers globally are already experimenting with generative AI in some form. In India, where speed and cost-efficiency dominate campaign strategy, the adoption rate is even higher across digital-first brands. Vishal Prabhu, Creative Controller at White Rivers Media, puts it bluntly, saying, “AI didn’t homogenize advertising—we did, by turning briefs into templates.”
His feed, like yours and ours, is a graveyard of “copy-paste culture in different fonts.” The culprit isn’t the machine. It’s the mindset. “When everyone feeds the same kind of prompt, sameness is inevitable,” he says.
And that sameness has a cost. Consumers don’t click on déjà vu. They tune it out. If everyone’s ad looks like everyone else’s, brand memory dies a slow, forgettable death. Prabhu’s team has a strict internal litmus test: if an idea feels like five other brands could’ve come up with it, it gets axed. Instead, they break down initial AI outputs and rebuild from the brand’s unique DNA. That tension between automation and originality, he says, is where real creative value lives.
Lloyd Mathias, business strategist and independent director, lays it out plain: “AI brings efficiency to the advertising process, particularly in data analysis and targeting. However, I caution against letting AI dictate creative decisions entirely. It’s critical to maintain a brand’s identity, and excessive dependence on AI could dilute the distinctiveness of advertising campaigns. AI should be strategically integrated into the advertising process, complementing human creativity rather than overshadowing it.”
Indeed, when algorithms start to dictate design language, tonality, and messaging—all optimized for what’s already performed well—you end up with advertising that’s more echo chamber than expression.
Rohit Agarwal, Founder and Director of Alpha Zegus, sees it playing out every day. “We’re beginning to see a wave of template-driven creativity—where campaigns feel polished, but often lack soul,” he says. “The speed and ease of AI tools have led to faster turnarounds, but also a tendency to over-rely on predictable formats, stock phrasing, and aesthetic symmetry. It’s like everyone is fishing from the same ideas pool.”
So, what’s the alternative? Enter brand-tuned AI.
Affle, for instance, has taken the challenge head-on. Their proprietary creative engine, OpticksAI, doesn’t just generate pretty templates—it adapts messaging and design in real-time, based on contextual signals and user behavior. More crucially, it’s trained on brand-specific assets. So, while the system might be churning out thousands of creatives, each one reflects the brand’s tone, identity, and personality. As Kedia explains, “This isn’t mass messaging—it’s nuanced, individualized communication.”
But even nuance has its limits when fed the same training data. Siddesh Hede, Marketing Lead at Rapoo India, sees it as a cultural risk, saying, “Many AI tools are trained on overlapping datasets, which can lead to outputs that lack cultural nuance or emotional depth.”
His team uses AI to ideate and iterate faster, but final calls rest with humans, and, critically, with local voices. “We work with local artists and creators who help us add that extra personal and cultural touch to our ads,” says Hede. “That’s not something AI can fake.”
This hybrid model—machine for speed, human for soul—is emerging as the only sane approach. Ajit Narayan, CMO at Socxo, agrees. “Content is far easier and AI is a boon… but campaigns have a big element of creativity. And yes, a small element of similarity is creeping up.” His team uses AI to reduce production time from weeks to hours, but never without human oversight, rejection rounds, and that messy process we used to call ‘thinking.’
There’s also the problem of what we’re training these tools on. If the source material is itself saturated with safe, middle-of-the-road content, then we’re feeding AI a diet of mediocrity and asking it to cook up magic.
As Manish Kumar, founder of Videos4Businesses, points out, “We see creative fatigue as many rely on a single AI platform, resulting in visual inconsistency and repetitive outputs.” His team now blends multiple AI tools with LoRA (Low-Rank Adaptation) training and layers that with human expertise across VFX, CGI, and direction—basically making sure the algorithm never gets the last word.
And then there’s the existential view. Bala Kumaran, Founder and Director at BrandStory, sees AI not just as a tool but as a kind of cultural bulldozer. In his words, we’re designing campaigns to please the algorithm, not the human subconscious. The more generative AI improves, the more it erases the messy, intuitive stuff that makes creativity click.
If every ad is optimized for a statistical average, then everything starts to look... average. To survive the sameness, brands will need to weaponize scarcity. And that means betting on the one thing algorithms still can’t fake: human originality.
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