Future of Marketing Briefing: AI’s branding problem is why marketers keep it off the label

And even that tally may be conservative. Not every use of AI is signposted. In some cases it sits in the production workflow rather than the storyline, embedded in editing, effects or optimization. Few marketers have much incentive to spotlight that. The reputational downside is clearer than the branding upside, which makes discretion the safer strategy. 

“I think advertisers are a little bit afraid of what kind of impact that has on consumers and their image with them,” said Nada Bradbury, CEO of AD-ID.

And who would blame them? 

The ads arrived amid a broader narrative that casts AI less as a novelty and more as a disruptor — one tied to job displacement, industry upheaval and intensified surveillance. No amount of creative finesse can fully paper over those fractures. Yes, it’s an assumption to suggest many marketers chose not to advertise their AI usage — but not an unreasonable one. Industry surveys over the past year, consistently show widespread experimentation with the technology across brands and agencies — its practically unavoidable at this point.

In that context, Bradbury’s conclusion carries weight: “I would venture to believe that AI usage within the creation of ads was much higher than we all know about but nobody’s willing to talk about it”

That silence is unlikely to lift anytime soon. As long as advertiser adoption continues to outpace consumer comfort, the incentive to downplay — rather than declare — AI’s role in advertising will remain one of its quieter truths. The Interactive Advertising Bureau has found that 82% of ad execs believe Gen Z and millennial consumers feel positively about AI-generated ads, while only 45% of those consumers say they actually do. The perception gap has widened since 2024, expanding from 32 percentage points to 37 in 2026 — a telling measure of how misaligned the industry’s confidence remains with audience sentiment. 

The IAB is trying to change that. It has been pushing for clearer guidance on when and how AI use in advertising should be disclosed, particularly around the circumstances under which marketers should make that information explicit. 

Its guidance is nuanced but really boils down to this: any ad that could plausibly mislead — for instance, using an AI-generated “customer testimonial” in an ad from a person who doesn’t exist — should be clearly labelled. 

The bar is intentionally high. Otherwise, blanket disclosures, such as tagging a video as AI-generated simply because subtitles were created using AI, risk diluting the value of transparencny and confusing audiences. If every minor assist — automated captions, background clean-up, color correction — caries the same “AI generated” label as a fully synthetic character or voice, the signal gets muddy fast. Viewers may start to treat the tag as either meaningless or boilerplate or, worse, as a warning label attached to otherwise ordinary creative. At that point, brands are not just over-disclosing, they’re flattening important distinctions. Over time, that could breed cynicism, where people assume AI is everywhere and inherently suspect, undermining both brand credibility and broader confidence in how the technology is being used.

How proven social creative is driving CTV spend

Ad tech companies tend to win at budget inflection points. The current shift isn’t just toward CTV or retail media. It’s toward scaling creativity that has already demonstrated performance. In that context, social platforms now function as large-scale testing grounds for that content, surfacing which messages and formats actually drive engagement. The opportunity, Nova’s leadership said, is operational: move those proven assets into CTV and the open web quickly and efficiently, using AI to adapt and distribute them rather than to invent something new.

The conversation below with Nova’s chief commercial officer Matt Barash has been lightly edited for brevity.

Digiday: What are you seeing in the market right now that proves that shift is actually happening—not just theoretically, but in live spending behavior?

Barash: What’s changed is that we’re no longer talking about this shift in the abstract. You can see it clearly in how campaigns are being built and where incremental dollars are going.

Culturally relevant moments are increasingly born in social, but the real spend shows up when those moments are extended into open-web video and CTV. Brands are rightfully using social as the ignition point for culture, not the finish line.

We’re seeing campaigns originate on platforms like TikTok and Instagram because that’s where modern cultural language forms fastest. But when something resonates, whether a creator-led narrative, a meme-driven insight or a moment tied to sports or entertainment brands are increasingly putting meaningful dollars behind that same creative across YouTube, premium publishers, and streaming environments.

A clear proof point is creator content. What used to be treated as “social-only” is now becoming hero creative for video buys. Advertisers are willing to pay higher CPMs outside the walled gardens because that content performs and feels culturally native even on the biggest screen in the house.

What’s notable is how little of this actually depends on flashy AI-generated creative. The real value of AI is largely unseen. The most effective use of AI in advertising operates beyond the naked eye. It shows up in how quickly winning creative is identified, adapted, sequenced, and redeployed across channels in real time. Another signal is speed. Brands are reacting to live moments in major sporting events, marquee awards shows and news cycles in social, then extending those same assets into open-web and CTV buys within hours or even minutes. Those aren’t experimental dollars. They’re planned budgets shifting to wherever optimization actually demonstrates compounding effective consumer reach.

Digiday: To what extent is that tied to the growing share of creator budgets going toward paid distribution and boosting rather than pure organic deals?

Barash: A lot of it is directly tied. Creator deals are increasingly just the starting point because brands aren’t buying posts, they’re buying outcomes. Organic reach is capped, so the fastest-growing part of creator marketing is the paid layer that scales what works beyond a creator’s native audience. The playbook is simple: prove it organically, then amplify it wherever incremental audiences live.

That shift is why Nova functions as a core utility rather than a point solution. Scaling creator content across paid environments is no longer a workflow problem, it’s an infrastructure problem. Nova sits at the intersection of social, programmatic and CTV, turning proven creator assets into modular, performance-ready creative that can move seamlessly from feed to open web to the living room. For brands, that means amplifying what already works without reinventing creative at every step. For publishers, it means monetizing creator-led storytelling with formats that feel native, premium and measurable across surfaces.

We’re well past experimentation. IAB estimates U.S. creator economy ad spend at roughly $37 billion in 2025 and climbing, with forecasts pushing into the mid-$40 billions in 2026. What matters isn’t just growth. It’s the mix shift toward paid amplification, both on-platform and off-platform. Creator content is no longer confined to the feed; it’s flowing into the open web and onto CTV as FAST channels and streamer partnerships expand. The implication is clear: creative that earns attention on a phone is now being scaled across the home, not because it’s been polished into something new, but because it’s already proven to resonate.

Digiday: In your model, where does revenue scale more predictably: direct brand relationships or agency-driven spend?

Barash: The most predictable revenue scale comes from agency-driven spend, but only as agencies evolve.

We’re deeply bullish on the agency, not as a traditional services business, but as a technology-enabled operating platform. The modern agency is becoming the system that orchestrates media, data, creative and measurement into a unified workflow that marketers rely on every day, not just campaign to campaign.

That’s where predictability and better business practices come from. When agencies own the workflow layer, spend isn’t as transactional by nature or tied to individual briefs. It’s embedded into how work actually gets done. Creative is no longer a one-off production cost, measurement happens in real time and optimization becomes continuous rather than reactive.

Nova is built to power that shift. We help agencies operationalize creative by turning social-first assets into scalable, addressable creative elements that move seamlessly across channels.. By automating adaptation, versioning, and performance feedback loops, we remove friction from the system and free teams to focus on campaign strategy, the art of storytelling and client impact.

In that model, AI doesn’t replace creative or strategic judgement. It amplifies it. Creative becomes infrastructure, AI runs quietly in the background and agencies gain leverage, efficiency and durability. When the platform becomes indispensable to daily operations, revenue scales more predictably and performance compounds over time. And everybody wins.

Numbers to know

59%: Percentage of U.S. teens aged between 13 and 17 that have used ChatGPT.

6.5 million: total number of posts about film and TV shared on TikTok every day in 2025, according to the platform.

10%: Percentage of monthly growth that ChatGPT is exceeding, according to CEO Sam Altman.

$1 billion: the annualized revenue generated by X subscriptions, according to its head of product, Nikita Bier.

What we’re reading

X Subscriptions Hit $1 Billion in Annualized Revenue, Exec Says
Elon Musk’s X platform has recently hit a $1 billion in annualized recurring revenue for its subscriptions, head of product Nikita Bier announced in an xAI all-hands meeting at the company on Tuesday, according to The Information.

Exclusive: OpenAI disbanded its mission alignment team
Recently, OpenAI got rid of its mission alignment team and the seven team members were transferred to other teams within the company, according to Platformer, while team lead Joshua Achiam has been named “Chief Futurist”.

Meta Hit By EU Warning to Open WhatsApp to Rival AI Chatbots
The EU has claimed Meta’s WhatsApp restrictions unfairly block competing AI assistants from gaining market access and fears the company policies could cause “serious and irreparable” AI competition harm, according to Bloomberg.

Why Brands Are Paying Creators Six Figures To Run Their Social Media
Brands, including Starbucks, ABC and John Deere, are now hiring creators full-time as polished corporate posts fail to compete with native content, according to Forbes.

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