Is ‘AI-powered’ becoming the industry’s most overused phrase?

There was a time when 'digital-first' sounded like a strategy. Then came 'data-driven,' 'omnichannel,' and 'purpose-led.' Each term had its moment. A window of genuine differentiation before the industry absorbed it, stretched it, and eventually rendered it meaningless. Now, 'AI-powered' is on the same curve. The difference this time, as several industry voices will tell you, is that the curve is moving faster than ever.

Walk into any product launch, brand refresh, or agency credentials deck today, and the word is inescapable. Smartphones are AI-powered. Refrigerators are AI-powered. Note-taking apps, customer service bots, and e-commerce search bars are all AI-powered. The label, once reserved for genuinely complex machine learning integrations, has become a packaging decision as much as a product one. The question the industry is now beginning to ask is no longer whether AI is being overused as a marketing claim (most agree it is) but what the cost of that overuse will eventually be.

The 'sticker phase' of the technology cycle

Suraj Nedungadi, Associate Vice President – Strategy at YAAP, has a blunt diagnosis for where the industry currently stands. "We are squarely in the 'slap a sticker on it' phase of the technology cycle," he says. "Every few years, we collectively find a new piece of vocabulary that cues innovation and disruption, and it makes the rounds across every organisation. We did it with 'organic,' we did it with 'blockchain,' and right now, if your toaster doesn't have an LLM, your brand is apparently prehistoric."

Nedungadi is not calling for restraint on the buzzword front. At least, not yet. From a pure growth standpoint, he argues, brands should ride the wave while it lasts. "If adding 'AI-powered' to your product description gives you a temporary lift in modern positioning or search visibility, do it," he says. The sharper point he makes, however, is that marketing cannot outrun reality forever. "The brands that survive the inevitable hangover of this trend will be the ones that used the buzzword phase to quietly fund and build genuine, utility-driven machine learning into their core offerings. If your AI doesn't actually solve consumer frustration, you are just buying temporary attention with an expiration date."

The broader industry data support the saturation argument. According to Jeel Gandhi, CEO of Under25, a youth-focused media and community platform, 83% of advertising executives have now deployed AI in their creative processes. That level of adoption (while impressive on paper) is precisely what drives homogenisation. When every brand is pulling from the same toolbox, optimising for the same metrics, and prefixing the same word to their product descriptions, the noise floor rises, and the signal disappears.

When the label works harder than the product

There is a diagnostic that several industry voices have independently arrived at: the moment the label is doing more work than the product, the positioning has already started to unravel. Roycin D'Souza, Senior Vice President – Branded Content at OML, frames it this way: "'AI-powered' starts feeling generic the moment the label is doing more work than the product itself. Slapping AI onto legacy automation isn't innovation. A customer service chatbot that still can't process a simple refund is just a bad experience with better branding."

D'Souza does offer a counterpoint: a case where the technology earns its mention rather than borrowing credibility from it. He cites Myntra's MyFashionGPT as an application that justifies the AI conversation not because of the technology itself but because of the experience it creates. "It took something as functional as e-commerce search and made discovery feel far more natural and conversational," he says. "That's interesting, not because it uses AI, but because it genuinely improves the journey. It was fun to use, and also helpful with making purchase decisions." The benchmark D'Souza is pointing to is a useful filter, and one that most current 'AI-powered' claims would struggle to pass.

Rajnish Rawat, Co-founder and CEO of Social Pill, a social-first creative agency, identifies what he calls a consistent pattern in the brands that are most aggressively pushing AI marketing: "Marketing teams moving faster than product teams. Brands attach 'AI' to their messaging because it signals modernity, but most of what's being labelled as AI is basic automation, rule-based personalisation, or a thin integration sitting on top of a third-party API. The claim leads the capability instead of following it." What Rawat finds telling is the inverse pattern: the brands doing the most substantive AI work tend to be the quietest about it. "They let the experience make the argument," he says. "And that's probably the clearest sign of where things stand right now — if you need to say it, your product probably isn't showing it."

AI fatigue, and the generation calling it out

If the advertising and marketing community is experiencing some degree of AI fatigue, the numbers suggest it is sharper among consumers, and sharpest among young ones. Jeel, who works closely with Gen Z audiences through Under25, points to a data point that should give AI-led brand strategies pause: 39% of Gen Z feel negatively towards AI advertisements. Broader consumer sentiment data adds texture to that figure.

The phrase 'AI slop' has increased ninefold in online mentions over the past year, with 82% of those mentions carrying negative sentiment. "Consumers are exceptionally perceptive, and they can spot machine-generated content instantly," Jeel says. "They are actively auditing brands — not just for what they claim, but for whether there is something authentically human about it."

The backlash is also beginning to shape brand strategy in ways that would have seemed counterintuitive two years ago. In a landscape where AI generation is the path of least resistance, choosing not to use it and saying so is starting to function as a premium signal.

Jeel is measured but clear about the underlying tension. "AI possesses immense power to execute critical analysis and complex creative thinking, and that capability is genuinely exciting. Used well, it should function as a collaborator that challenges perspectives, sharpens original ideas, and expands what is creatively possible. The challenge is that many brands are skipping that potential entirely and using AI to generate the output rather than elevate the thinking behind it." The result, he argues, is a wave of synthetic copy and automated visuals that lack cultural nuance and emotional resonance, and audiences are noticing.

From differentiator to infrastructure

The longer historical view may be the most clarifying one. Nedungadi draws a parallel that strips the current moment of any exceptionalism. "Innovation loses its magic the moment it becomes standard infrastructure. Think about high-speed internet. In the early 2000s, businesses proudly advertised 'Broadband-powered operations' to look cutting-edge. Today, if a company bragged about using electricity or having a website, you would question their sanity rather than applaud their innovation. AI is on the same trajectory. It will soon become the invisible plumbing of the digital world."

Rawat plots essentially the same trajectory from a different vantage point. The 'organic' label was once a genuine differentiator. Then came 'sustainable,' then 'digital-first.' Each got stretched until it meant something between very little and nothing at all. "'AI-powered' is on the same curve, just faster," he says. He also flags that the fatigue is not uniform across audiences. Mass-market consumers may still respond to AI as a capability signal, but younger cohorts and B2B buyers are already asking sharper questions. What does it actually do? How does my experience change? "The brands that win this next phase will compete on demonstrated outcomes, not declared capabilities."

Meanwhile, D'Souza notes that the first wave of AI anxiety (fear, hesitation, surface-level experimentation) has largely passed. "The conversation has matured," he says. "The more serious work has begun: figuring out where AI actually adds meaningful value." That work is quieter, less marketable, and probably more consequential than anything currently carrying an 'AI-powered' badge. The industry seems to sense this, even if the communications have not caught up.

Rawat's assessment of the timeline is characteristically direct: "The 'AI' label had maybe a 24-month window as a real differentiator. That window is closing. What comes next is simpler: does the product work or doesn't it?" That reset from declared capability to demonstrated experience is where the next round of brand competition will be won. The brands that used the buzzword phase to build real utility will have something to show for it. The ones that only slapped a sticker on it will find that the sticker has stopped doing any work at all.