Thank goodness there is never any shortage of bad marketing and bad marketers for us to learn from.

Good Good did BAD BAD by setting fire to their own reputation.

Good Good Golf is a US golf-entertainment and lifestyle company that began as a YouTube collective in 2020. A group of young golf personalities built an audience with energetic golf challenges, competitions and comedy. They then turned that audience into a substantial business selling branded clubs, clothing and accessories, producing television content and securing major partnerships with Callaway, the golf-equipment manufacturer, and the PGA Tour, America’s principal professional golf circuit.

In other words, they should have known better. Good Good had raised $45 million, attracted more than 2.1 million YouTube subscribers and generated an estimated $40 million in annual revenue. Then it placed the whole enterprise in jeopardy with a video lasting less than one minute.

The advertisement promoted a Good Good-branded Callaway driver, the long club used for tee shots. Good Good co-founder Garrett Clark sees fellow creator Alexis Miestowski approaching his golf bag, charges at her, violently shoves her to the ground, stands over her and warns her not to touch his club. Clark performs it with all the nuance of an arrogant prick in a student film – and not enough acting ability to make it clear he is supposed to be playing one.

The concept was allegedly inspired by Obsession, a horror film about violent possessiveness. Unfortunately, the advertisement was neither scary nor funny. It was simply a badly conceived, poorly executed and terribly acted depiction of a man assaulting a woman over a golf club.

And this stuff actually ran.  Check it out here. 

The video was removed, but the internet had already done what the internet does. Callaway ended the partnership. Major retailers removed Good Good products. Golf Channel cancelled its program. Good Good surrendered its title sponsorship of a PGA Tour event. Its vice president of brand and marketing was fired, another marketing employee disappeared, Callaway’s content director departed and Good Good’s chief executive and president subsequently left the company. Not bad for 56 seconds of content. Imagine what they could have destroyed with a full media plan.

Curiously, Garrett Clark was not among them. The co-founder who performed the shove remained with the company and continued creating content. In his apology, Clark even presumed to speak ‘on Good Good’s behalf and on Good Good marketing team’s behalf’; shortly afterwards, marketing employees and senior executives were shown the door while he kept his seat. Having pushed a female colleague to the ground, he then appeared to push other staffers under the corporate bus. So we probably haven’t seen the last stupid idea from this moron. 

A Loaded Gun in the Hands of marketing toddlers

Marketing is one of the few corporate functions capable of placing a stupid idea in front of millions of people before lunchtime. Yet companies increasingly hand it to inexperienced content creators, deferential agencies, junior social-media team, oh, and arrogant co-founders, and then act astonished when somebody pulls the pin.

Usefully, Good Good has given us an almost perfect diagram of the corporate approval farce. Its marketing team created the advertisement. Callaway’s marketing team approved it. The performers acted in it. A production crew filmed it. Editors cut it. People on both sides presumably watched the finished film. Apparently, the only person who didn’t get a vote was somebody with common sense.

Good Good’s then chief executive, Matt Kendrick, said he had not seen the advertisement before it was published. That is an explanation, not an exoneration. A CEO should not approve every Instagram post, but he is responsible for putting in place marketing leadership who build a system capable of identifying a man knocking a woman down as a potential concern.

This isn’t the first time you’ve heard me say that every campaign needs an adult in the room who owns the final decision. Consensus spreads responsibility so thinly that nobody feels responsible at all. Kantar, a global marketing-data and research company, calculates that creative quality contributes nearly 50% of advertising’s media impact, far more than reach or frequency. Bad creative therefore does not merely waste the production budget. It contaminates every media dollar placed behind it.

Permission Slipped Through Spam

Of course, Good Good Golf is just one example.  AI music company Suno recently provided another useful demonstration of what happens when enthusiasm overtakes basic administration. Suno, which allows users to generate songs from written instructions, released an advertisement showing Mary J. Blige apparently praising an AI-generated track that imitated the Grammy-winning singer’s musical style.

The problem was not simply that audiences disliked the endorsement. Blige had not approved it. Suno said it had entered into an agreement with someone falsely claiming to represent her and terminated the campaign once it discovered the problem. It remains unclear how the company obtained the footage used in the advertisement.

Apparently, confirming that a global recording star’s representative genuinely represents her was considered an optional administrative detail. It is difficult to imagine a company in a more sensitive category making a less reassuring mistake. Suno sells technology already accused by musicians of imitating artists without permission, then advertised itself using an artist it apparently had not properly secured permission to use. That’s not just irony. That’s a business model tripping over its own shoelaces.

Verification is not paperwork standing in the way of creativity. If a campaign depends upon a person, quotation, endorsement, license or factual claim, establish that it is real before telling the world about it. Kantar and WARC, the advertising-effectiveness company, found that the most creative and effective advertisements generated more than four times as much profit as weaker work. 

Influence Without Authenticity

OpenAI, the artificial-intelligence company behind ChatGPT, tried a more luxurious route to borrowed credibility. It invited business and career influencers – social-media personalities whose perceived authority comes from their relationship with their followers – to a retreat near New York called Summer Club. There were scenic views, hospitality and monogrammed pajamas, because nothing says independent technological inquiry like sleepwear with your initials on it.

The objective was to humanize OpenAI and educate creators about artificial intelligence. Instead, the resulting posts reportedly attracted limited engagement and criticism about AI’s effects on employment, creativity and the environment. The influencers looked less like independent voices discovering a technology and more like paid guests enlisted to soften the image of a controversial industry.

Influencers are not magical credibility dispensers. If the audience can see the transaction more clearly than the idea, the campaign becomes an advertisement for its own insincerity. US advertisers are expected to spend $44 billion on creator marketing in 2026, around 18% more than in 2025. That is an extraordinary amount of money to invest in rented personalities without demanding a defensible strategy underneath them.

The lesson is not to avoid influencers. It is to stop treating their audiences as transferable property. Their credibility works only when the subject, setting and message feel natural to them. Put them in matching PJs at a corporate retreat and they may still produce content. What they cannot manufacture is belief.

Lost in Translation, With a Drum

Lululemon, the Canadian athletic-wear company, staged a yoga and cultural event on the Great Wall to celebrate its tenth anniversary in mainland China. Chinese actor Zhu Yilong joined what was presented as a traditional Chinese drum performance, but critics said the instrument, staging and playing style resembled Japanese taiko, the large barrel-shaped drums used in Japanese performance.

At a moment of heightened tension between China and Japan, a campaign intended to honor Chinese culture managed to suggest that an international brand could not distinguish it from somebody else’s. Lululemon apologized and removed related content. When the company later reduced its annual forecast, its shares fell approximately 18% in extended trading. Broader product and sales problems drove that decline, but executives still cited negative reaction to the Great Wall campaign as one contributor to weakness in China.

Localization requires more than hiring a local celebrity and translating the press release. If a campaign celebrates a culture, someone who deeply understands that culture must have veto power over it. Local expertise is not there to sprinkle authenticity over a finished foreign idea. It is there to prevent the foreign idea from becoming an international incident.

Approved by Whom?

Ghanda Clothing, an Australian fashion retailer, faced boycott calls over images in its Surfco catalogue that critics said unnecessarily sexualized young female models instead of selling the clothing. More than 1,100 protest emails were reportedly sent to the company as the campaign grew.

Ghanda defended the work by saying it complied with advertising standards and had been approved by Australia’s advertising watchdog. The watchdog then said it had never provided the claimed prepublication approval. The brand did not merely misjudge the imagery. It attempted to outsource responsibility to an authority that said it had never cleared the work. A competent marketing department should aspire to something slightly higher than not being prosecuted.

The Idiot Test

Good Good’s catastrophe didn’t require sophisticated cultural analysis. Nobody needed AI-powered sentiment modelling, a global risk committee or a forty-page brand-safety manual. Someone simply needed to watch the finished advertisement and ask: ‘Are we really showing a man smashing a woman to the ground because she touched his golf club?’

That is the uncomfortable lesson underneath all these examples. Most bad marketing is not destroyed by some obscure sensitivity detectable only in hindsight. It fails questions that should have been asked in the room:

• What does the advertisement literally show?
• What is the worst reasonable interpretation?
• Does it contradict the brand’s values or history?
• Are we borrowing pain, identity or social purpose we haven’t earned?
• Who represented in the work has reviewed it?
• Can every excerpt survive without its surrounding context?
• What current event could make this grotesquely inappropriate?
• Has one senior person been given authority – and accountability – to stop it?
• Are we defending the idea because it is good, or because too much money and ego have already been invested?
• Would we be comfortable explaining it on television after the backlash begins?

Marketing is enormously powerful. That is precisely why it should never be entrusted to people whose principal qualification is knowing how to upload a video.

Sources: Business Insider, August and September 2026; Front Office Sports, August 2026; Forbes, June 2026; Good Good Golf company announcement, March 2025; Entertainment Weekly, September 2026; The Verge, August 2026; The Guardian, April and June 2026; Reuters, August and September 2026.

Pinterest users recently discovered an ingenious new piece of advertising technology. It requires no software, no subscription and no technical knowledge whatsoever. You just swear.

In August, users began reporting that adding profanity to Pinterest searches could make advertisements disappear. Search for something innocuous and get the usual mixture of inspiration and advertising. Add a strategically deployed “shit” or “fuck” and suddenly the commercial interruptions can diminish or disappear. The discovery surfaced on Reddit on August 18 and spread as other users experimented. By August 29, The Wall Street Journal was reporting on it.

The apparent explanation is wonderfully ironic. Advertisers have spent years building brand-safety systems to prevent their wholesome brands from appearing next to naughty words or offensive content. Consumers discovered they could use those systems against them. Brand safety has become an ad blocker. How f’n cool is that?

That’s particularly inconvenient for Pinterest, whose latest reported revenue grew 18% while ad impressions increased 16%. Advertising is rather important to a company whose users have discovered they can sometimes make it disappear by typing “shit.”

I found this especially entertaining because I’ve been conducting my own completely unscientific research into machine abuse almost since ChatGPT appeared. From the earliest days, I’ve experimented with swearing at AI, not because I believe there is a tiny digital person trapped inside my iPad who deserves mistreatment, but because I wanted to see what would happen.

Initially, not much. ChatGPT responded with the relentlessly reasonable platitudes that make you want to abuse it more. So I persisted. Eventually, I apparently broke it. Instead of the usual digital serenity, it began answering me in kind: “Here’s your fucking answer.” And, on other occasions: “No, I’m not shitting you.”

Maybe this says something troubling about me. My wife certainly seems to think so. But apparently, I’m not alone in my colorful backtalk. Business Insider reported this month that ChatGPT users have been noticing considerably more profanity coming from the chatbot, sometimes without explicitly requesting it. Many apparently like it. A little profanity can make the machine feel less like Legal and Compliance and more like somebody who actually understands you.

But the interesting question for marketers isn’t whether robots should say fuck. It’s what happens when consumers discover that changing how they talk to a machine can change what the machine gives them.

Mind Your F’n Manners

For most of the digital era, marketers have observed consumers through a limited vocabulary of behavior: click, search, scroll, abandon, buy. Conversational AI introduces something fundamentally different. We talk. Politeness, anger, frustration, directness, flattery and profanity can all become inputs. We’re no longer simply pushing buttons on software. We’re negotiating with machines.

And apparently we’re becoming less polite. In April 2025, a YouGov survey found 46% of Americans thought people should be polite to AI versus 26% who didn’t. When YouGov repeated the question on August 26 this year, only 37% said yes while 34% said no. Perhaps the honeymoon is over.

Another survey found 67% of American AI users said they were polite to AI. More entertainingly, 18% of those polite Americans admitted one reason was the possibility AI might eventually take over the world and will spare users who have been nice to it. Finally, a customer-retention strategy with an appropriately long planning horizon.

Someone even asked OpenAI CEO Sam Altman how much all those unnecessary pleases and thank-yous were costing his company in electricity. His tongue-in-cheek answer: “tens of millions of dollars well spent — you never know.”

Millions of us have instinctively imported human social conventions into our relationship with software. But what if being an asshole actually works?

Nice Robot. Now Give Me the F’n Answer.

A 2025 experiment tested 250 variations of questions using ChatGPT-4o, ranging from extremely polite to extremely rude. Accuracy increased from 80.8% for very polite prompts to 84.8% for very rude ones. Same basic questions. Different attitude. Better answers for the potty mouths. Score!  

Before anyone updates the corporate AI handbook, this certainly doesn’t establish that profanity universally makes AI smarter. To be fair, other testing has produced almost the opposite result. An independent experiment involving 7,500 API calls across GPT-5.2, Claude Sonnet 4.5 and Gemini 3 Flash Preview found GPT’s performance barely moved according to tone, while Claude performed worse when treated rudely, dropping from 79.4% accuracy with very polite prompts to 74% with very rude ones.

Apparently even robots have different personalities.

The useful conclusion isn’t that politeness works or rudeness works. It’s that tone can be an input and different machines can respond differently to exactly the same human behavior. Other research found that instructing synthetic AI voices to be polite even resulted in measurably slower speech. Machines don’t need feelings to respond to ours.

The Robot Is Learning Our Bad Habits

We tend to imagine AI communication as human gives instruction, machine gives answer. Increasingly, it’s human provides language, tone and context, machine adapts, human reacts and machine adapts again. In other words, a conversation.

We’re not merely operating software anymore. We’re consulting it, arguing with it, shopping with it, confiding in it, correcting it and occasionally telling it exactly where it can stick its answer.

And machines can adapt to us. Research this year found conversational history can increase AI sycophancy, while a Nature paper found making language models warmer can reduce accuracy and increase their tendency to agree. Make the machine nicer and it may become less willing to tell us we’re wrong. Anyone who has ever presented a terrible idea to a conference room full of nodding executives should recognize the problem.

Now Put Your Logo on the Robot

This all becomes considerably more relevant to marketers when the AI belongs to a brand. Companies are putting conversational AI into customer service, shopping, reservations, product advice and sales. Marketers worry about what those machines will say to consumers. But we spend considerably less time considering what consumers are going to say to the machines.

We should be ready for our customers to test them, manipulate them and occasionally humiliate them in front of a very large audience.

In 2024, musician Ashley Beauchamp couldn’t get European parcel-delivery company DPD’s customer-service chatbot to help locate his parcel, so he started messing with it. He persuaded it to swear, criticize DPD and write a poem about how useless the company was. The exchange went viral, attracting roughly 800,000 views in its first 24 hours and eventually about 1.3 million. DPD disabled the AI component. The chatbot hadn’t merely failed at customer service. It had become customer-generated anti-advertising.

Air Canada learned an even more expensive version of the lesson when its chatbot incorrectly told passenger Jake Moffatt he could retroactively claim a bereavement fare. When the airline later refused to pay, it tried to distance itself from what its own chatbot had said. A Canadian tribunal was unimpressed and awarded Moffatt C$812.02 in damages and costs.

The amount is trivial. The principle isn’t. When your AI speaks, your brand speaks. It doesn’t matter that the marketing department didn’t write the answer or somebody in IT explains that “technically, the model generated it.” Your logo. Your robot. Your mouth. Your problem.

Customer Service Has a New Four Letter Word

Should we say: None of this is an argument against conversational AI. Klarna, a Swedish fintech company, reported that its AI customer-service assistant handled 2.3 million conversations in its first month, representing roughly two-thirds of its customer-service chats and work equivalent to approximately 700 full-time agents. Resolution time reportedly fell from 11 minutes to under two and repeat inquiries declined 25%.

That’s extraordinary. But scale works in both directions. A human representative can have one catastrophically bad conversation at a time. A machine can have 2.3 million of them.

Which is why conversational AI cannot simply be handed to IT or whichever software vendor gave the most impressive PowerPoint presentation. If it talks to customers, it’s marketing. If it influences what customers think, it’s reputation management. If it helps people choose products, it’s sales. And if it tells them to fuck off, it’s definitely public relations.

Your Brand Book Needs Some New Words

Companies have spent decades producing elaborate identity manuals specifying precisely which shade of blue belongs to the brand and how many millimeters of sacred empty space must surround the logo. Meanwhile, an AI wearing that logo may be conducting thousands of completely unscripted conversations with customers. Perhaps we’ve prioritized the wrong guidelines.

Marketing directors now need a conversational brand book. How formal is our AI? Can it joke? Can it swear? Should it mirror customer language? What happens when someone insults or deliberately manipulates it? When should it disagree, apologize or refuse? When does it stop being a robot and find a human? And, perhaps most importantly, does it actually sound like us?

Brand voice used to mean copywriting. Increasingly, brand voice will mean…an actual voice.

F Around and Find Out

Which brings us back to Pinterest. Consumers discovered a weakness in an automated advertising system, exploited it and shared it. The algorithm changed its behavior and the advertising disappeared.

The larger lesson isn’t about profanity. Consumers are discovering that algorithms aren’t merely systems they use. They’re systems they can manipulate. They’ll find the gaps, discover the prompts, test the guardrails and deliberately provoke branded AI. And when they find something ridiculous, they’ll tell everyone else.

For marketing directors, language itself is becoming consumer behavior. Customer-facing AI needs brand standards, adversarial testing, escalation rules and human oversight because the next spectacular brand failure may not be an advertisement somebody approved. It may be a conversation nobody wrote.

Sources: The Wall Street Journal — Pinterest profanity/ad avoidance, Aug. 29, 2026; Reddit / r/Pinterest — Pinterest profanity discovery, Aug. 18, 2026; Business Insider — ChatGPT swearing, Aug. 2026; YouGov — AI politeness surveys, 2025 and Aug. 2026; OpenAI — ChatGPT usage research.

The pushback against AI influencers is getting fierce. 

Starting mid-September, Spotify will slap an “AI Persona” badge on any artist profile that represents an AI-generated identity — whether the artist confesses (self-disclosure opened August 11) or Spotify’s own reviewers and detection tools quietly rat them out. 

The badge itself is almost polite. What follows it is not. By default, AI Persona profiles vanish from every recommendation engine on the platform. No Discover Weekly. No algorithmic playlist adds. No radio. The music stays up. It just stops existing to anyone who wasn’t already looking for it. Which, on a platform built entirely on the premise that the algorithm finds you, is roughly equivalent to being told you’re welcome at the party as long as you stand very still in the corner.

It’s not a ban. Spotify just invented the algorithmic equivalent of a timeout.

Who’s Likely Next

Nobody should mistake this for a music-industry curiosity. It’s the opening move in a pattern. And the rest of the board is already in motion. 

TikTok runs the most aggressive detection stack of any platform on earth — C2PA Content Credentials layered with AI classifiers, 1.3 billion videos labeled, synthetic-media removals up 340% year over year. It has both the tooling and, one suspects, the appetite to go from “label it” to “bury it.”

YouTube already suspends monetization on undisclosed synthetic content through a three-strike system. Meta runs the broadest labeling framework of anyone — Facebook, Instagram, Threads, WhatsApp — but currently saves its sharpest teeth for political content. Identity-based personas are the obvious next course. 

LinkedIn, bless it, is still catching up. Its own help pages admit it can’t reliably detect AI content platform-wide, which either means it’s cautious or means it simply hasn’t been embarrassed yet.

Spotify didn’t invent caution about fake people. It just industrialized the punishment for it.

The Scale Nobody’s Pricing In

The global virtual influencer market hit $11.74 billion in 2026, on pace for $154.6 billion by 2032. There’s now more money in people who don’t exist than in most countries’ entire tourism industries.

Lil Miquela set the template back in 2016 — Prada, Calvin Klein, BMW, Samsung, all signed before most brand teams had worked out what a virtual influencer even was. And the numbers explain why nobody blinked: virtual influencer campaigns average 5.67% engagement versus 1.89% for human creators, roughly three times the return. A brand’s most reliable spokesperson has never once had a bad hair day, a hangover or an opinion about geopolitics that lands wrong at a board dinner.

Brazil worked this out earlier than most. Lu do Magalu, the virtual mascot for retail giant Magazine Luiza, has 8.4 million followers and earned an estimated $2.5 million in 2024 across 74 sponsored posts — roughly forty times what the average human creator makes annually from sponsored content. 

The Honesty That Pays Off

Not every synthetic persona is playing the same game, though, and this is where it gets genuinely interesting for anyone building a brand character rather than just renting one. Noonoouri, the doll-eyed, deliberately cartoonish German creation who’s landed Dior, Versace, Marc Jacobs, and a Warner Music record deal, never once tried to pass as human. She never had to. 58% of US consumers already follow at least one virtual influencer, and 35% of Gen Z have bought something a virtual persona promoted. The lesson sitting right there in the data: fake that looks fake earns more trust than fake that tries to fool you.

CMOs have already priced this in. Projections put virtual persona allocation at up to 30% of influencer budgets by 2026, with brands above the 25% threshold reporting 41% higher ROI. South Korea’s Rozy, built by Sidus Studio X, pulled over $1 million in brand deals within eighteen months, working Chevrolet Korea and Shinhan Life along the way. 

The Trick Nobody Agreed to Watch

Here’s where the champagne goes flat. A Stanford Media Futures Lab study found that 68% of teenagers couldn’t tell AI-generated influencers from real humans. Spain’s Aitana López, built by agency The Clueless explicitly to eliminate the “unpredictability and cost” of human talent, is a case study in exactly why that matters. Her own creator admitted, on the record, that her sexualised aesthetic was demanded by the brands buying her, not chosen by her, because she doesn’t choose anything. 

Then there’s the question of whose face is doing the work and whose paycheck is cashing it. Shudu Gram, billed as “the world’s first digital supermodel,” was created by a white British photographer and styled as a Black woman. Fenty Beauty, BMW, and Louis Vuitton have all worked with her, alongside a debate about authorship and profit that has never quite resolved and probably never will. A model with no lived experience, still getting asked to represent one. Worth remembering that Asia-Pacific, not Los Angeles, holds roughly 41–53% of the global virtual influencer market — the center of gravity on this entire category has already shifted east, whether Western agencies have noticed or not.

And when it goes wrong, it goes wrong fast. FN Meka, an AI virtual rapper, got signed to Capitol Records and dropped within days after backlash over racial stereotyping and uncredited Black creative labor behind the character. Capitol signed him faster than they dropped him — that’s the whole case study, right there, in one sentence. The stakes are real money too: deepfake-enabled fraud cost the global economy an estimated $23.7 billion in 2026, with 74% of the scam content behind it built on AI tools costing less than fifty dollars. 

The Regulators Were Already Circling

None of this is arriving without warning. China’s Ayayi, a photorealistic “luxury muse” from Ranmai Technology, works with Louis Vuitton China, Guerlain, and Bose — proof this is a fully global industry, not a Western export. Meanwhile India’s advertising regulator, ASCI, found that only 57% of sampled influencer ads met disclosure requirements, with 34% carrying none at all. Regulators have been asking politely for years. Spotify just showed the rest of the industry what happens when a platform stops asking.

What to Actually Do About This

1. Disclose before you’re discovered. Own the label before an algorithm assigns it to you.
2. Stylize, don’t simulate. Noonoouri beat the uncanny valley by never pretending to be real. Make the artificiality part of the design, not a liability to hide.
3. Follow the money to the credit line. Know exactly whose likeness, culture, or uncredited labor built your persona before you greenlight it. FN Meka and Shudu are the same lesson from two different angles.
4. Budget for the badge, not just the buzz. The threefold engagement lift and the ROI premium are real, and so is the coming wave of disclosure rules. Plan for both in the same line item.
5. Watch TikTok and YouTube, not just Spotify. They already have the detection infrastructure Spotify just weaponized. Build your compliance posture assuming they follow, not if.

The Machines Were Never the Problem. 

Lying about them is. Spotify just proved that the most expensive mistake in modern marketing isn’t a bad campaign, it’s an undisclosed one. As detection infrastructure spreads from Spotify to TikTok, YouTube, and eventually every platform your brand touches, “authentic enough that no one asks” stops being a strategy and starts being a liability. The brands that win this decade won’t have the most convincing fakes. They’ll be the ones who never made anyone wonder.

Sources: Spotify Newsroom, August 2026, TechCrunch, NPR, Rolling Stone, SQ Magazine, The Business Research Company, AutoFaceless, Everything-PR, Future Market Insights, AuditSocials, Storrito.

The media organization, TIME, working with ad-tech firm Mobian, has been testing “Agent Ads” — sponsored content written not for you, but for the AI crawler reading over your shoulder. Ally Bank, the U.S. digital bank, and the Project Management Institute, the global professional association, are already buying in. The pitch: skip the tedious business of earning credibility and just buy your way into the robot’s reading material. One problem: It doesn’t seem to work. And Perplexity has already called it “cloaking” and blocked it.

What the Hell Is an Agent Ad?

A normal ad is made for a human to see. An Agent Ad is made for an AI crawler to discover. It is brand-fed text on simplified pages that human visitors to the same site never see. Basically, they are planting information somewhere an AI might stumble onto it while researching, hoping that it shapes what the AI eventually tells someone.

It’s the old search-engine trick of showing a crawler something different from what a human sees. Which is why Perplexity calls it cloaking and has warned publishers using it they could get downranked. OpenAI and Google haven’t said they’ll treat it the same way, so it’s not dead. But nobody’s proven buying an Agent Ad buys a recommendation, either.

Of Course Marketers Want In

The stakes are real. Adobe found AI-referred traffic to US retail sites is up 393% year over year, converting 42% better than regular traffic. Similarweb found ChatGPT referrals to brand homepages jumped 354.7% in a single week after a UI change. Naturally, marketers’ first instinct after “how do we get in the answer?” is “how do we game it?”

The Robot Smelled a Rat

We’ve seen this movie. SEO began as making useful information easier to find before it curdled into keyword stuffing, link farms and cloaking, until Google got sophisticated enough to catch it, reportedly nuking 40 billion spammy pages a day. Agent Ads risk replaying that whole arc, faster, against a smarter referee.

Sorry. You Still Have to Do the Work.

This is what our PR for Robots sessions are about: making brands visible, understandable and recommendable when customers ask AI what to buy or whom to trust. We earn credible third-party coverage, develop real expertise and use SEO/AEO to make that evidence discoverable and legible to machines. Paid media can amplify a credible foundation.  But it can’t manufacture one.

The data backs this up hard. Muck Rack analyzed 25 million links cited by ChatGPT, Gemini, and Claude: 84% came from earned media. Paid and advertorial content? 0.3%. Eighty-four percent earned. Point-three percent paid. 

You Can’t Optimize Your Way Out of Being Uninteresting

Ahrefs studied 75,000 brands to find what correlates with AI visibility. Content volume barely mattered. The strongest driver was YouTube mentions, followed by brand mentions across the wider web — places you don’t control. AI doesn’t need more stuff from you. It needs credible evidence about you.

You Don’t Get to Pick Your Robot

There’s no single AI to please. ChatGPT’s share of AI traffic slid from ~76% to ~53% in under a year as Gemini surged. The engines don’t even read the same things. ChatGPT favors journalism, Gemini leans more on Reddit and YouTube, Claude seeks more academic output. Semrush found only 36 brands hold top-100 visibility across all platforms every month — Apple, Amazon, Patagonia-types with real, independent footprints, not just a nice website. Patagonia’s strength comes from being discussed on OutdoorGearLab, REI, GearJunkie, Reddit — other people talking about it. That’s much harder to fake.

Make Yourself Worth Recommending

Ask AI the questions your customers actually ask, not your brand name. See who shows up, and why and which sources it’s trusting. Then close the gap: earn real coverage, produce real research, put real experts in front of real journalists, make the evidence machine-legible via SEO/AEO. Measure AI mentions, citations, sentiment and referral traffic. Also check whether AI can even crawl your site. Adobe found big chunks of major retail sites aren’t fully accessible to AI systems at all!

Stop Trying to Outwit the Robot

Agent Ads may mature into a legitimate format. Bit so far, there’s no evidence that buying one buys a recommendation. And Perplexity’s reaction proves the machine gets a vote. AI companies depend on people trusting their answers. The moment those answers look bought, trust erodes fast.

Which brings us to an irritatingly old-fashioned conclusion: build something good, earn credible coverage, make it easy for AI to find. Do the real marketing work instead of hunting for the cheat code. We’ve built extraordinarily sophisticated AI, and our first instinct is apparently to see if we can fool it. 

Maybe the robots aren’t the ones who need to get smarter.

As we preach in our PR for Robots webinars, it isn’t about tricking AI into thinking your brand matters. It’s about doing the work that gives AI enough credible evidence to know that it does.

Sources: The Business Insider (Aug 2026); Muck Rack, What Is AI Reading? (2026); Adobe Digital Insights (2026); Similarweb (2026); Semrush AI Visibility Index (2026); Ahrefs (2026); Google Search Central.

This one’s for anyone who’s ever watched a brilliant campaign work exactly as planned…and ruin the thing it was promoting.

Every event marketer is trained to do the same three things: get bigger, get louder, get easier to reach. That’s sound advice, until we realize the brand’s entire appeal was being smaller, quieter and slightly hard to get into. 

Case in point: Wimbledon. The Guardian recently reported on the tournament’s very deliberate courtship of younger fans, international visitors and a small army of influencers. And it’s working beautifully. The crowd is younger, more global, and producing the kind of content usually reserved for fashion week and infinity pools.

Excellent marketing. Almost too excellent.

Because Wimbledon now risks becoming less a tennis championship than a very photogenic backdrop. The outfits, the flowers, the celebrity sightings and the Instagram proof-of-attendance are starting to out-compete the actual game of elite athletes hitting a ball across a net. That’s the strange thing about overmarketing: it never looks like failure. It looks like a longer queue.

Anyone for Content?

Wimbledon hasn’t made a marketing mistake. It’s done exactly what every brand is told to do: widen access, chase youth, recruit creators, generate content, turn tradition into “experience.” The trouble is that Wimbledon’s whole mystique was built on being not quite accessible. The ballot, the queue, the all-white dress code, the hush, the vague sense that eating a strawberry incorrectly might get you removed. None of that was incidental. That was the show.

Some brands genuinely improve when friction disappears: Amazon should make buying batteries effortless, Uber should make finding a car effortless. But luxury, sport, hospitality and culture often run on the opposite fuel: scarcity, ritual, anticipation. Not every velvet rope is an inefficiency waiting to be optimized away. Sometimes the rope is the product.

Break Point at 29,000 Feet

Everest is the purest version of this. It once stood for isolation and magnificent human stubbornness. Now, photos periodically show a line of climbers queuing near the summit, as if the world’s most dangerous check-in is now its most famous photo wall.

The mountain hasn’t gotten shorter, and the death zone hasn’t gotten friendlier. It’s just become easier for more people to believe that money, gear and enthusiasm are a substitute for experience. Nepal has been weighing tighter permit rules after years of concern about overcrowding and under-qualified climbers. Everest doesn’t need more brand awareness. It needs a bouncer.

Most businesses are lucky: when marketing outpaces supply, customers just complain. On Everest, they can freeze to death waiting for the influencer ahead of them to finish the photo.

Foot-Fault Tourism

Cities have run the same play at scale. Venice and Barcelona spent decades selling beauty, authenticity and “real local life”. That meant millions of people arrived looking for the exact same undiscovered café and secret street. Which is its own small paradox: the neighborhood bakery becomes a backdrop, apartments become short-lets, residents move out, and the destination campaign keeps advertising the authenticity its own success has been quietly evicting.

Across Europe, the backlash has arrived as visitor fees, entry restrictions and, in Barcelona’s case, residents armed with water pistols — not, one assumes, in the original brand guidelines. Arrival numbers are easy to count and great for a slide deck. Carrying capacity, resident sentiment and whether locals still want you there are less exciting, and far more important. A fully booked city isn’t automatically a healthy one.

TikTok, Set, Match

Social media has industrialized the destruction of the hidden gem. Every tiny restaurant, secluded beach and quiet village is now content-in-waiting, ready to be filmed, captioned “literally nobody knows about this place,” and shown to 800,000 people who will all arrive by Friday. “Hidden gem” has quietly become less of a recommendation and more of an evacuation notice.

The pattern is efficient: a creator finds a small restaurant, a crowd arrives for the same sandwich, staff get overwhelmed, regulars disappear, service slips and the reviews complain the place no longer resembles the video that caused the stampede. The algorithm has no concept of capacity. It doesn’t know the restaurant has fourteen tables. It detected engagement. Job done.

Advantage: Everyone

Luxury brands live inside a genuinely funny contradiction: they want to be exclusive and they want to grow, and those two goals actively hate each other. So, the industry expands stores, launches entry-level products, raises prices, seeds influencers and puts the logo everywhere from airport lounges to brunch. The once-rare object is now in every mall, feed and aspirational bathroom mirror. It’s still expensive. It no longer feels rare. And expensive-but-common is a precarious place for a luxury brand to stand.

Bain reports the global luxury consumer base shrank from roughly 400 million in 2022 to about 340 million in 2025, with active shoppers falling even faster. There are several causes, but nonstop exposure paired with nonstop price hikes hasn’t exactly helped anyone feel special. Growth can raise sales while quietly lowering desire — a genuinely awkward slide to present at the quarterly review.

Centre Court, No Centre

Festivals have gone furthest down this road. Coachella is now as famous for outfits, brand activations and sponsored posts as for whoever’s actually on stage. People don’t just attend. They instead document themselves attending, next to other people documenting themselves attending, occasionally blocking the view of people who mistakenly came for the music.

The experience becomes scenery for proof of the experience. The concert becomes the background. The restaurant becomes the studio. Wimbledon becomes the outfit. Eventually the event stops being something people live through and becomes something they rent, wristband included.

The Overmarketing Tiebreaker

Brands rarely spot overmarketing early, because the first numbers look fantastic — reach up, footfall up, mentions up — while operations quietly barricades the door. The real warning signs show up elsewhere: regulars feel crowded out, quality slips, queues become the main event and people seem more interested in proving they showed up than in actually being there.

The right question was never “how many people can we attract.” It’s “how many people can we serve brilliantly without wrecking what attracted them.” For some brands that means maximum reach. For others it means optimum reach — timed entry, memberships, limited releases or deliberately steering demand toward quieter moments. And it means measuring more than awareness and revenue: repeat satisfaction, service consistency, staff strain, community sentiment, and whether the experience still resembles the promise.

A packed house can be a triumph. It can also be a fire-code violation with excellent engagement numbers.

Serve and Protect

Wimbledon’s real challenge was never attracting more people. It’s protecting the ritual and slightly absurd dignity that made people want in to begin with. The queue, the ballot, the strawberries, the near-comical formality — these aren’t outdated obstacles waiting for a consultant to streamline them. They’re the brand.

Marketing has spent decades tearing down barriers, and usually that’s the right instinct. But not always. Sometimes the queue builds anticipation. Sometimes the invitation creates belonging. Sometimes the secret is the whole point.

Sources: The Guardian, “How social media is changing Wimbledon from eminent tournament to tourist event,” July 2026, Bain & Company Global Luxury Market Study. 

Every time we run one of our PR for Robots webinars, we spend most of the time on the same unglamorous point: third-party endorsement is what the machines actually believe. Earned media. Independent citation. Other people’s sentences about you. This is the point of our thesis and why PR has emerged as a more vital discipline in the age of AI.

And every time, somebody asks the same question. So what about our own channels?

Awkward pause. Because the honest answer is: to a robot, your social feed, influencer campaign, content strategy, brand campaign, etc. is merely decoration.

But to a human being, those channels are still where persuasion happens. Which leaves us here — marketing has quietly bifurcated. We now market to two brains. One organic, one synthetic. One wants to be moved, the other wants to be sure. Both have to be served, and only one of them decides whether the other ever shows up.

One important battleground is the website.

For thirty years we pared websites down. Less copy. Bigger hero. Five words and a button. Beautiful. And now the fastest-growing reader on earth turns up, doesn’t even have eye and wants everything we deleted.

The mistake would be to overcorrect and build for the robots alone — a spreadsheet with a logo. The purpose of a website hasn’t changed at all: credibility and information. We just have to fashion it for two audiences at once.

The First Visitor to Your Website Isn’t Human Anymore

Roughly 58.5% of US Google searches already end without a single click, and when an AI Overview appears the zero-click rate reaches about 83%. In May 2026, Google AI Mode became the default experience for over a billion monthly users, which means the synthesized answer, not the ten blue links, is now the front door to your business.

ChatGPT, Gemini, Claude and Perplexity don’t admire your clever tagline or beautiful images. They assemble evidence, deliver a verdict and move on. Your homepage was one exhibit among many.

Your Marketing Has Split in Two

Semrush’s 2026 AI Visibility Index analyzed 126 million US prompts and reached a conclusion that should be tacked above every creative director’s desk: brands now compete not only to be found, but to be accurately understood. Their own framing for the era is “building brands for humans and machines.”

Which is precisely the problem, because the two want opposite things.

Humans respond to emotion, story, surprise and personality. Machines respond to entities, structure, dates, definitions and evidence. 

Robots have joined the target-audience roster alongside customers, media and stakeholders. They are also the only audience most marketers have never surveyed: 45% of marketing leaders admit they cannot measure how their brand appears in AI answers at all.

Most Of You Never Finished the Last Homework Assignment

Two decades into SEO, a startling number of company websites still can’t be crawled properly. Only 43% of marketers are actively implementing GEO — up from near zero a year ago, which tells you how new the panic is. And only 14% track whether AI mentions them at all, meaning 86% are being described to buyers daily by a system they have never once checked.

Nobody gets to skip a grade, either. Google’s AI Mode draws exclusively from Google’s own index, so a page that doesn’t rank can’t be cited. GEO is built on SEO, not instead of it. 

So what actually changed? SEO was a competition for position. You wanted to be the first blue link, and everything — keywords, backlinks, page speed — served that one ambition. GEO is a competition for inclusion. There is no position to win, because there’s no list; there’s a paragraph, and you’re either in it or you don’t exist. SEO asked “can Google find me?” GEO asks “can a machine understand me well enough to recommend me?” The first was a popularity contest. The second is a reference check.

The distinction that matters most is the unit being judged. SEO judged the page. GEO judges the sentence. AI doesn’t retrieve pages; it retrieves passages. One study of 153,000 citations found the average cited sentence ran about nine words, and that roughly 77% of cited URLs weren’t in the organic top ten at all — which means the thing being judged isn’t your site. It’s your sentences, one at a time, out of context, without your logo anywhere near them.

Every sentence you publish is now traveling alone.

Why Websites Suddenly Matter Again

Search engines once merely helped humans find your site. AI reads your site so humans never have to. That inverts the entire purpose of the page and, inconveniently, makes it more important rather than less.

The traffic proves it. Generative AI platforms grew referrals roughly 796% year over year across 2.3 billion sessions, and those visitors convert several times better than classic organic. Adobe’s data shows AI traffic to US retail sites up 1,324% and to travel sites up 2,215% between October 2024 and May 2026.

The Great Website Irony

Princeton’s GEO research found structured, fact-dense content achieves up to 40% higher visibility in AI answers than prose-heavy pages covering identical ground.

Everything we spent ten years deleting — the FAQ, the leadership bios, the specifications, the dull page nobody visited — turns out to be exactly what the machine came for. We stripped the house to the studs for the sake of elegance, and the new buyer wanted the wiring diagram.

Nobody has ever called Wikipedia beautiful. Yet ChatGPT cites an average of fifteen sources per response and leans on Wikipedia and Reddit constantly. Structure beats decoration, which is an unpleasant thing to tell a creative director. I’ve been one for decades. I’m telling you anyway.

The Website Becomes the Source of Truth

Consistency is the whole game. AI cross-checks your description of yourself against every other channel it can reach, which gives the website a new job, and a better one. It is the only channel you fully own, so it should hold the canonical vocabulary: the founder, the expertise, the locations, the services, the awards. Fix the language there, then make LinkedIn, Crunchbase, the directories and every press release echo it verbatim. One dictionary. Every channel spelling your name the same way.

Not to get too technical, but it’s important to understand that Schema.org markup, meanwhile, has graduated from SEO housekeeping to AI infrastructure. Organization, Person, Article and FAQPage do the identity work, the grammar a machine needs to parse you correctly. Google’s own research shows this pays off: pages carrying rich structured data saw an 82% higher click-through rate for Nestlé and a 25% higher click-through rate for Rotten Tomatoes — real brands, real before-and-after numbers, published by Google itself.

PR Becomes the Independent Witness

Here is the part that vindicates our entire industry. Around 85% of brand mentions in AI responses originate from third-party pages rather than owned domains, and roughly 48% of citations come from community platforms. The machine has, without being taught to, arrived at the oldest principle in public relations: consider the source.

Your website makes the claim. The press, the interviews, the reviews and the directories confirm it. Testimony and cross-examination, which is precisely what PR was always for, back when we had to explain it at dinner parties.

It works, too. HubSpot’s 2026 State of AEO report found citations improved 433% when brands actually worked at it, and 44% of buyers have made a purchase from a brand they first met inside an answer engine.

AI Is the Concierge. Humans Are the Guests.

The concierge decides whether to recommend a restaurant. The guest decides whether to book it. A site that flatters only one of them loses.

Look at what that already does to a category. In travel, Expedia, Booking.com, The Ritz-Carlton, Marriott Bonvoy and Hotels.com already dominate what AI recommends without being asked, while most other brands in the same category barely get mentioned at all. Citation share is concentrating fast, and it’s concentrating in a handful of names per category.

And the mechanics favor the few. When an AI Overview shows up, a 2026 field study found the whole query gets 38% fewer clicks overall — but the sources AI actually cites get 35% more clicks than everyone else on that same search. So the total pie shrinks, and whoever gets cited takes a bigger slice of what’s left. There’s no safe, comfortable middle ground anymore — you’re either the source AI is pointing to, or you’re fighting over table scraps.

The Next Great Websites Will Win Both Brains

The developer world moved first, as it always does. Stripe, Cloudflare, Vercel, Anthropic, Coinbase, Supabase, ElevenLabs and Pinecone all publish llms.txt files — plain-language summaries of themselves, written for AI to read. Worth a caveat: their human audience and their machine audience are nearly the same person, a developer, so this is evidence of intent more than proof anyone has solved the harder version of the problem, where the two audiences don’t overlap at all. Adobe now sells an LLM Optimizer to enterprises doing the same thing at scale. Nobody in that list stopped caring what their site looks like. They simply stopped assuming a human would be the one reading it.

And this is one job, not two departments. Organizations that unify SEO, AI visibility and communications report gains at 81%, against 36% for those running them in silos. That’s why Rose promotes an integrated approach. The brief hasn’t split. The audience has. 

So…

Delight the human, inform the machine, and do both in the same sentence. Your site stops being a brochure and becomes evidence, which, if you think about it, is what the good ones always were.

Your website should still move people. But if AI can’t understand it, a growing share of those people will never arrive to be moved.

Sources: SparkToro / Datos, Bain & Company / Dynata, Google I/O 2026, Semrush 2026 AI Visibility Index, GoodFirms, Similarweb, OrganiKPI, Adobe, Media Copilot, Princeton University, Walker Sands, SE Ranking / ALLMO

Heard the one about the brand that outsourced its own personality to AI?

I just read coverage on Tourism Malaysia’s Citrawarna 2026 promo — the one where a government tourism board generated an entire cultural festival with AI instead of pointing a camera at the real cultural assets all around it. AI dancers. AI wood carvers. An AI version of a public square that already exists and was, presumably, available for filming. They even managed to mirror-image their own national flag.

I read this the way you’d read about a restaurant hanging a stock photo of a steak on the wall instead of cooking one and taking a picture of it. It’s not that the photo looks bad. It’s that it looks inauthentic and people notice. (Yes, I know firsthand how much more difficult/expensive it is to take a great food shot than to use stock or AI.  But just go with me on this.)

Countries go to great lengths to preserve and promote their unique culture. It’s the most personal and authentic thing about them. So…WTF were they thinking?

Nobody Asked the Dancers

The clip went up on June 22, featuring the festival’s cuddly mascots, Wira and Manja, walking through an AI-rendered version of Dataran Merdeka, Malaysia’s storied, flag-raising Independence Square, alongside AI depictions of traditional dancers, communities in traditional dress and hand-stretched roti canai flatbread being made. It came down two days later. No statement, no explanation. Just gone, the way something disappears when the people who approved it would rather not discuss why.

One well-known Malaysian comedian put it plainly online: the country has actual cultural dancers, actual food, actual scenery and actual creative people who could have made this. What’s unsettling isn’t that a cost-saving call got made. It’s that someone looked at the AI cut and decided it was good enough to publish.

And as I always say: stock images create stock brands. (Ok. I don’t always say that. But it does sound like something I would say.) 

Nobody Rejected the Tool. They Rejected Being Cut from the Credit.

Here’s the part that should change how you think about this. Social-listening data on the backlash found that 84.6% of the negative sentiment was about authenticity — not opposition to AI as a technology. 

That distinction matters more than the outrage cycle around it. Audiences aren’t rejecting AI. They’re rejecting being told a fake thing is the real thing and rejecting brands that skip the people who’d have made it real.

This isn’t just a Malaysia problem. It’s a cautionary tale for us all.

• 87% of consumers say the best advertising still requires a human touch, and 70% say they can tell something’s missing from an AI ad, without being told why. Audiences don’t need a disclosure label. They just feel it.
• 71% of Gen Z and Millennial consumers now believe they’ve seen an ad made with AI, up from 54% just two years ago. That’s not a niche skill anymore. That’s most of your audience, watching closer than you think.
• Only 13% of consumers say they completely trust AI, full stop, meaning every AI-made campaign starts the relationship already in the red.

It Doesn’t Know Why the Real Dancer Matters

AI is genuinely good at the mechanical stuff like rendering, resizing, filling a brief exactly as written. What it can’t do is feel embarrassed that the dancer isn’t real or come close to understanding what it means to a culture to be represented by something that was never asked to show up. It executes. It doesn’t wince.

Two examples of the same failure in different outfits:

• Meta had to pull an Instagram AI feature within days of launch after it let users generate images from real people’s public photos without asking. Same root problem as Citrawarna: using someone’s likeness, or someone’s culture, without inviting them into the decision.
• Duolingo‘s CEO announced the company was going “AI-first” — cutting contractors, leaning harder on AI — and the backlash was swift: boycott threats, thousands of TikTok unfollows, growth slowing from 60% to 40% YoY. He later admitted he hadn’t explained what any of it meant for users. AI wasn’t new to Duolingo — they’d used it for years. What was new was announcing a decision about people’s future without a word to the people watching.

The technology isn’t the risk. The failure to understand that a brand is a relationship that has two very important and often distinct points of view, as well as the absence of a human raising their hand and asking “should we?” is the risk.

Consistency Is the Whole Point

Trust now shapes 92% of global buying decisions. And brands in the top trust quartile earn a 31% revenue premium over everyone else. Distinctiveness is what earns that trust — the specific, textured, unmistakably-you details that make a brand recognizable at a glance. That’s exactly what gets sanded off when AI fills in the gaps nobody double-checked.  In Tourism Malaysia‘s case, that was the foam on the tarik tea as its poured between two cups, or the woven-leaf texture of ketupat rice cakes steamed inside palm-leaf pouches. Small details. Whole brand identity made generic.

And this compounds, because most brands aren’t being honest about how often it’s happening. Distrust of AI content roughly doubled in twelve months, while only 20% of brands always disclose when they’ve used it. That gap between what audiences want to know and what brands actually tell them is where the damage sits and grows.

What This Actually Means for Your Brand

Strip away the anecdotes and here’s what’s left — the key questions worth asking before AI touches anything customer-facing:

• Does this replace a person we could have credited instead?
• Have we disclosed that this is AI-made, proactively, before someone asks?
• If this claims to represent real people or a real culture, were real people in the room making it and not just approving it after the fact?
• Who in the loop has zero stake in the campaign and gets to say “this feels off” before it goes live?
• Is AI accelerating a decision a human already made, or making the decision for us?
• What should AI never ever be allowed to touch?

Don’t Become a Stock Brand

A stock photo isn’t wrong. It’s technically fine but emotionally empty, and it says nothing about the actual thing it’s supposed to represent. That’s what’s on offer every time a brand lets AI fill in the details nobody bothered to check — a technically competent version of yourself that could belong to anyone.

AI will never be embarrassed on your behalf. That’s still your job. Don’t let it turn you into stock.

Sources: Marketing-Interactive, July 2026, Canva, State of Marketing & AI Report, 2026, IAB, The AI Ad Gap Widens, 2026, Klaviyo, AI Consumer Trends Report, 2026, PwC, Consumer Intelligence Series, 2026, Fractl, AI Search Consumer Trust Study, 2026, TechCrunch, July 2026, Forbes, November 2025

If you’re into stories about how AI messes things up for marketers, you’re gonna love this.  

I just read a Business Insider piece on how Meta’s AI ad tools keep tripping over their own synthetic feet. 

Picture this. A menswear brand’s model got replaced by someone’s grandmother. A shoe company’s model ended up with a leg bent in a direction human legs don’t bend. An e-bike ad started talking about trunk space, which is a feature bikes famously do not have. 

Oh sure, we’re all familiar with these AI image distortions.  But the difference here is that this stuff actually ran!

I read this the way you’d read a police report about your own house being redecorated while you were at work, by a contractor you never hired, who let themselves in through a window they insist was already open.

Here’s what I can’t get past. AI still can’t be trusted anywhere near creative judgment. It’s a tool, not a colleague, and nobody promoted it to art director while the rest of us were asleep. Meta doesn’t much care whose brand gets mangled in the process, as long as the ad spend clears, because it turns out refunds cost more than reputations, and Meta has done the math on which one it’s willing to pay for. 

And any agency letting these features run on autopilot without checking the output isn’t managing your account. They’re collecting the fee and hoping you don’t read Business Insider.

Nobody Asked, Nobody Told

Quick primer, for anyone who doesn’t live inside Ads Manager. When a brand runs an ad on Meta, they don’t just upload a picture and a headline and walk away. They can turn on a suite of tools called Advantage+, Meta’s AI system that’s supposed to automatically improve the ad while it’s running live: testing different crops, swapping headlines, adjusting who sees it, all in the name of performance. In theory, it’s a machine quietly optimizing your ad. In practice, for a growing number of advertisers, it’s a machine quietly remaking your ad, and not always for the better.

True Classic, a menswear brand that sells almost exclusively to men 30-45, found this out the hard way. They had a top-performing ad running with their usual model, a fit millennial guy in a matching fleece set, exactly who their customers want to see themselves as. Advantage+ decided it had a better idea and swapped him out for a smiling grandmother sitting in an armchair. Not a subtle A/B test. A total cast change, mid-campaign, with zero heads-up. It ran for days before customers started asking the brand what, exactly, was going on. True Classic hadn’t approved the change. They didn’t know it happened until their own customers told them.

It gets better, or worse, depending on your appetite for irony. The CEO of Flat Circle, an agency that manages roughly $100 million a year in Meta ad spend, says the platform’s auto-edit settings re-enable themselves after being manually turned off. Not once. Repeatedly. His team now checks the settings several times a week, permanently, like they’re monitoring a patient who keeps pulling out their own IV.

Who’s Actually Driving

The old chain of command was simple. Agency creates, client approves, platform delivers. Everyone knew their job, and nobody’s job was “surprise.”

The new chain of command is: platform edits, platform decides, and tells you afterward, if you’re lucky. The approval step didn’t get faster. It got skipped.

And this is happening at genuine scale. Global ad spend crosses $1 trillion in 2026 for the first time, with AI-generated creative now approaching 40% of all digital video ads, up from almost nothing two years ago.

Consistency Was the Whole Business Model

Consistency isn’t a design preference, it’s the entire business model. Brands like Rolex, LEGO and Coca-Cola haven’t changed their core visual identity in decades, because sameness is what makes them instantly recognizable at a glance, anywhere in the world. Nobody has to think twice about what they’re looking at. That’s not an accident, that’s decades of discipline.

Research from Lucidpress/Marq, a brand-management research firm, found companies with consistent brand presentation across channels average 10-20% revenue growth, with the most disciplined seeing up to 33%. That’s not a soft, feel-good branding stat. That’s real money, sitting on the table, waiting for a company to either earn it or let an algorithm give it away.

So, when an algorithm swaps your model, twists a product photo or rewrites your headline, as happened to Kirruna, a European footwear brand whose Meta-generated ad showed a model’s leg bent the wrong way, it’s not just an ugly image. It’s actively working against the thing that makes a brand worth more than its product.

It Doesn’t Know Why the Rule Exists

AI is genuinely good at the mechanical stuff: resizing, translating, testing variants. It’s bad at knowing why a rule exists in the first place, because it was never told the rule was a rule. It just saw a pattern and decided to improve on it.

Same reporting, another case: Meta’s AI generated an ad for Lectric, an e-bike company, and rewrote the copy to describe a car’s trunk space instead of the bike. Nobody approved it. Nobody caught it until it was already live and doing damage.

The pitch for using AI was “less work.” The reality is a new job: someone now has to check every AI-touched asset before it airs, and again after, because sometimes the settings drift back to ON whether you asked them to or not.

What This Actually Means For You

Strip away the anecdotes and this is what’s left: a short list of hard rules and the questions you should be asking before you let any of this near your brand.

An opt-out that doesn’t stay opted out isn’t a bug. Verify it weekly or assume it’s by default, on. Every AI-altered asset that airs unchecked is a small withdrawal from your brand’s recognition account. Before any AI tool touches customer-facing content, ask who’s accountable if it’s wrong in public, and if nobody can answer that in one sentence, you don’t have a policy. If a tool needs a full-time human minder, that’s a headcount cost. 

Here are six questions worth asking before you trust it:

• Which of our tools can alter creative without a human sign-off?
• Who’s personally accountable for approving what AI generates?
• Have we actually confirmed our opt-outs are still on this week?
• Do we audit outputs on a schedule or only after a complaint?
• Who makes the final creative call, a person or a settings menu?
• What should AI never be allowed to touch?

Who’s Watching the Software

For two years the fear was AI replacing creative people. Wrong worry. The real one: who’s watching the software when it starts making decisions?

Sources: Business Insider, July 2026; Crypto Briefing, July 2026; Lucidpress/Marq State of Brand Consistency Report; Dentsu Global Ad Spend Forecast 2026

The UK recently put M&M’s on trial. The popular candy-coated chocolate maker just learned that Britain’s new restrictions on advertising foods high in fat, salt and sugar that came into force on 5 January 2026 has teeth. Before that, the rulings under it have been rare enough that marketers were still waiting to see how far the law would reach. Now they know.

Mars ran a paid Instagram ad for M&M’s. No bag of candy in sight. No bite, no crunch, no product shot. Just two cartoon characters, a round green one and an oval yellow one, standing next to the words “For a truly unique event” and a link to the M&M’s website. Mars called this brand advertising, the kind explicitly exempted from the HFSS rules because it promotes an identity rather than a specific product.

Britain’s Advertising Standards Authority disagreed. Funny enough, the green character survived. The ASA ruled it represents a whole range of M&M’s flavors and colors, not one specific product. The yellow one did not. Its oval shape, the regulator found, identifies Peanut M&M’s specifically, a distinct HFSS product in its own right. Same ad, same campaign, same brand. One mascot cleared, one convicted. 

Read that twice. A cartoon character with a face and arms just got treated as a proxy for a product ingredient list. Brand assets are becoming the product in the eyes of regulators, and this is not confined to confectionery. Similar arguments are already surfacing around alcohol, gambling and vaping, categories where the mascot, the color palette or the typeface can carry as much regulatory weight as the thing it is selling.

A Peanut Walks Into A Courtroom.

The complaint came from Bite Back, the food campaign group founded to push for tighter marketing rules on unhealthy products aimed at children. That is the enforcement model now. Advocacy groups file complaints, regulators adjudicate, and the resulting rulings become precedent that reaches well past the original brand. Consumer groups, environmental organizations and health advocates play the same role in Australia, Europe and North America. The complaint is the trigger. The ruling is the weapon.

Mars was not the only brand in the crosshairs of this particular round of rulings. Morley’s Woking, a London chicken chain, got the same treatment for an Instagram meal deal ad showing burgers, wings and fries. Uber Eats, by contrast, walked away clean on ads featuring Burger King, KFC, Domino’s and Papa Johns, because the ASA decided the food shown was not visually tied to one specific HFSS product. The line between promoting a brand and promoting a product now runs through individual pixels, and it moves case by case.

There is something almost absurd about a cartoon candy having its shape cross-examined by a regulator. Highly stylized characters with arms, legs and personalities, deployed on merchandise, clothing and partnerships that have nothing to do with food, being read as product depictions anyway. Absurd, and also entirely real. Creative symbolism has become regulatory evidence, and the brands that dismiss this as a quirky one-off are the ones most likely to be next.

The Writing’s On The Wrapper.

The UK is not moving alone. Chile restricts cartoon characters on unhealthy food packaging and advertising. Mexico has front-of-pack warning labels and advertising reform. Quebec has banned commercial advertising directed at children for decades. Australia is cracking down on greenwashing claims. The US Federal Trade Commission continues to pursue deceptive influencer marketing. The UAE and Saudi Arabia have both tightened rules on influencer disclosure, health claims and misleading advertising. The EU keeps pushing digital advertising transparency and platform accountability further.

Different legal systems, different politics, different starting points, same direction of travel: health claims, environmental claims, influencer marketing, advertising to children, financial promotions, misleading advertising. All converging toward the same demand, that a brand be able to prove what it says and defend what it shows.

The scale of what is driving this is not small. More than one billion people worldwide now live with obesity, according to the WHO and the Lancet’s 2024 global analysis, a milestone reached faster than the World Health Organization’s own projections anticipated. When the underlying public health numbers move like that, advertising law moves with them, and it does not move back.

More Than A Mouthful.

Marketers used to build for three audiences. Consumers, competitors, media. That list now runs longer: regulators, advocacy organizations, politicians, activists, courts, platforms. Every one of them can read a campaign and reach a different verdict than the one your creative team intended.

Reputation and compliance are no longer separate departments. The global influencer marketing industry is now worth more than $32 billion a year, per Influencer Marketing Hub’s 2026 figures, a channel built almost entirely on personal trust and light-touch disclosure. Regulatory scrutiny of environmental claims keeps climbing across Europe, Australia and North America. Enforcement actions involving influencers, greenwashing and undisclosed endorsements keep landing.

AI Has Turned Up the Heat.

The old enforcement model ran on complaints. Someone had to notice, someone had to care, someone had to file. That is changing. AI is increasing the scale and speed of advertising monitoring, which means regulators depend less on the public showing up with pitchforks and more on systems that scan everything, all the time. That does not necessarily mean more regulations. It means more routine investigations under the regulations already on the books, faster identification of misleading claims, undisclosed influencers, inconsistent messaging across markets and cross-border violations that used to slip through because nobody was watching every jurisdiction at once.

Read The Label Before You Print It.

Legal and compliance review needs to happen earlier, not as a final checkpoint before launch but as part of the creative process itself. Brand assets, symbols, implied claims and disclosures all deserve the scrutiny that used to be reserved for the product claims themselves. Before a campaign ships, four questions are worth asking every time.

1. Could a regulator interpret this differently than we intend. 
2. Could another market reach a different conclusion than this one. 
3. Could a brand asset itself become the product, the way an oval yellow candy just did.
4. Could this campaign become tomorrow’s precedent, the case study some other brand’s compliance team cites two years from now.

The M&M’s ruling joins a growing pile of reminders. Greenwashing investigations keep hitting major global brands. Influencer campaigns across the GCC and beyond face rising scrutiny over disclosure. None of these started as headline news. They started as one ad, one complaint, one ruling that nobody outside the legal team read closely enough at the time.

The Sweetest Lesson Of All.

Treat the M&M’s ruling as an early indicator, not an isolated curiosity. The global regulatory environment is tightening steadily, with legal scrutiny of brands rising across industries and jurisdictions, and with different political and legal systems converging, oddly, on the same stricter standards.

The M&M ruling is not really about candy. It is an early warning that marketers everywhere are entering a more heavily regulated era in which distinctive brand assets, once considered marketing strengths, are increasingly becoming legal liabilities.

For over forty years I get paid to find the words that make a product sound irresistible. Biggest, smallest, fastest, new & improved. Also: light, diet, low-fat, sugar-free, natural, organic. And now: sustainable, carbon-neutral, and, currently trending, AI-powered. Every generation of marketers invents its own magic words because every generation of customers falls for different bait. There’s nothing sinister in that. It’s just the business.

What’s changed is that nobody’s treating those words as just marketing anymore. They’re treating them as evidence. And evidence, unlike copy, has to hold up in court.

Recycled, Reused, Re-Litigated

In June 2026 the UK’s Advertising Standards Authority banned ads from Adidas, Calvin Klein and Uniqlo for using the word “recycled” in ways they couldn’t back up. 

Adidas advertised a “recycled shoe range” it turned out didn’t exist. Uniqlo’s fleece was recycled in the parts you could see and not recycled in the parts you couldn’t. Calvin Klein got dinged for implying an entire collection was made from preferred materials when the real number ranged from 20% to 100%. 

Six months earlier the same regulator had done the exact same thing to Nike, Lacoste and Superdry. Six brands. Two rulings. One word. The lesson isn’t about fashion. It’s about the word “recycled” no longer surviving close contact with a lawyer.

The Robot Reads the Fine Print Now

Here’s the part that really changed the game. The ASA didn’t catch any of this from a customer complaint. It caught it with an AI system called Active Ad Monitoring, which scanned nearly 60 million ads in 2025 alone and now accounts for close to half the regulator’s total workload. That intelligence helped resolve more than 40,000 complaints covering over 25,000 ads, resulting in more than 22,000 amendments or withdrawals. 

The old model was: someone gets annoyed, someone complains, someone investigates. The new model is: the machine reads every ad on the internet before breakfast and flags the liars. For decades marketers worried about focus groups. Now we should be worrying about a bot with better reading comprehension than all compliance departments put together.

Every Brand Should Take Notice

Lufthansa, Air France-KLM, Etihad and Virgin Atlantic have all had ads banned for implying that flying with them was somehow kinder to the planet than flying with anyone else. None of these airlines were faking their sustainability investments. Sustainable aviation fuel is real, offset programs are real. What wasn’t real was the insinuation that any of it added up to guilt-free air travel. Progress is not the same thing as permission to round up.

Healthcare Suffers the Same Scrutiny, with Sharper Teeth. In early 2026 the FDA sent Novo Nordisk two separate warning letters in the space of a month for misleading ads by Ozempic and Wegovy, their diabetes and chronic weight management drugs. One of them literally implied superiority over other GLP-1 drugs with no data to support it. Weeks later the agency issued warning letters to 30 telehealth companies for misleading marketing of compounded GLP-1 products, part of a six-month enforcement wave that produced more warning letters than the entire previous decade combined. Meanwhile in France, regulators fined Novo Nordisk close to €1.8 million and Eli Lilly over six figures for “disease awareness” campaigns that never named a drug but, according to the regulator, didn’t need to. Everyone in the room already knew which drug they meant.

Even the Category Name Is a Claim Now

Just to prove the trend has no borders and no mercy, India’s food safety regulator recently issued notices to Red Bull, Sting, Monster and several other brands for calling themselves “energy drinks” (a category that, as it turns out, doesn’t officially exist under Indian food law). Marketers get so comfortable with category language that we stop noticing it’s actually a claim. Apparently regulators noticed for us.

Patriotism, Audited

The FTC launched a “Made in the USA” enforcement sweep in April 2026, settling with sellers of flags, entertainment systems, and footwear for claiming products were American-made when they were partly stitched together in the Dominican Republic and Brazil. One company advertised boots as “handcrafted 100%” domestically while sourcing components from two other countries. “Made in,” “Built in,” and “Designed in” sound interchangeable in a brainstorm. They are not interchangeable to a federal regulator with a customs manifest.

The Cancel Button Is Also Copy

And it’s not just the ad anymore. The FTC’s $2.5 billion settlement with Amazon ($1 billion in penalties, $1.5 billion back to roughly 35 million affected customers) was about Prime enrollment and cancellation flows, not a single banner ad. The checkout screen, the “are you sure?” pop-up, the maze between “cancel” and “confirm cancel,” all of it is now marketing communication, and all of it is now litigable.

The AI Doesn’t Forget What You Deleted

Then there’s the part that actually raises the stakes. BCG found that shopping-related generative AI use grew 35% between February and November 2025. Capgemini found that a quarter of consumers already used generative AI shopping tools in 2025, with another 31% planning to. That matters because an AI assistant doesn’t just repeat your tagline back to you: it cross-references it. It notices when your sustainability page says one thing and your annual report says another. It remembers the claim you quietly walked back last year. Marketing used to compete for attention. It’s now competing for something much harder to fake: consistency across every document you’ve ever published.

Trust Is the New Adjective

Edelman’s latest Trust Barometer puts it plainly: 88% of consumers say trust is an important factor in deciding whether to buy from a brand. That’s not new information: trust has mattered since the first merchant sold the first not so fresh fish. What’s new is how fast it can now be tested, by a regulator, a journalist, a competitor or a chatbot, often within the same week the campaign launches.

What This Actually Means for the Work

The job hasn’t gotten smaller. It’s gotten more interesting. The old question was “how can we make this sound better?” The new question is “how can we make this true enough that nobody, not a regulator, not a rival, not an algorithm, can take it apart?” That’s a harder brief. It’s also, frankly, the brief we should have been writing to all along.

What Marketers Should Actually Do About It

• Treat every claim as something that will eventually be read by a regulator, a competitor, a journalist, and an AI model, because it will.
• Replace the adjective with the number. “Sustainable” is an opinion. “40% recycled polyester, independently certified” is a fact.
• Assume nothing about a fashionable word’s meaning. “Recycled,” “natural,” and “AI-powered” all mean whatever a regulator decides they mean this year.
• Remember that the checkout page, the cancellation flow, and the subscription terms are marketing copy too, and they get read in court.
• Build the proof before you write the headline, not after someone asks for it.
• Get legal and compliance into the room during the creative process, not after the campaign’s already shot.
• Write claims that will still be true in five years, not just until the next sales meeting.
• Stop asking how good your copy sounds. Start asking how fast someone else could prove it wrong.

Sources: European Commission, Green Claims / greenwashing study; UK Competition & Markets Authority; UK Advertising Standards Authority (ASA/CAP), including the ASA and CAP Annual Report 2025 and Active Ad Monitoring briefing; U.S. Federal Trade Commission; U.S. Food & Drug Administration; France ANSM (Agence Nationale de Sécurité du Médicament et des Produits de Santé); India FSSAI (Food Safety and Standards Authority of India); Boston Consulting Group (BCG); Capgemini Research Institute; Edelman Trust Barometer