AI-generated advertising has stopped being a pilot program. According to IAB's latest research, developed with Sonata Insights, generative AI is now firmly embedded in how brands produce creative content, not as an experiment on the side, but as a default part of the workflow. The numbers back this up: 86% of buyers are already using, or planning to use, generative AI to build video ad creative, based on IAB's 2025 Digital Video Ad Spend & Strategy Report.
That statistic alone tells you the adoption conversation is largely over. The more interesting question the report raises isn't whether brands are using AI creatively but why and whether that "why" is quietly changing the kind of advertising we're all producing.
Adoption is no longer uniform; it's channel-specific
According to the report, the share of advertisers using AI for various formats of ads is distributed unevenly. As for social media ads and display ads, 85% and 73% of the advertisers, respectively, are using AI. Meanwhile, for TV and audio ads, the corresponding numbers are 56% and 42%, respectively.
That gap is not random. In fact, it maps very closely to the concept of risk and reversibility. Social and display are very fast-moving environments that are easily changed and are highly iterative. This means that even weak AI-generated content can be changed within a day and often within hours. In contrast, TV and audio are high-risk, high-cost environments to produce, hard to test at scale, and mistakes are highly visible and can be permanent.
For brands looking to bring AI into their creative pipeline first, it’s worth bearing in mind this pattern. Start with the cheap iteration and fast feedback of social and display; build up some institutional knowledge and get comfortable with AI before moving on to the harder-to-reverse, higher-stakes TV and audio ads.
The motivation behind AI adoption has quietly shifted
Here's the part of the report that deserves more attention than it's getting: the reason brands are adopting AI creatively has changed significantly in just two years.
The primary benefit of using AI in advertising has shifted to cost efficiency in 2026, stated by 64% of the respondents. Two years prior to that, in 2024, cost efficiency ranked 5th. As for creative innovation, the benefit is still valued by 61% of the respondents and therefore not ignored. However, it is no longer the primary driver as it was before.
That’s a meaningful pivot. Just two years ago brands were experimenting with AI to generate better ideas, such as novel visual approaches, to explore more ideas, and to test out more ideas than they could have manually. Today cost-efficient ideas are the main driver: more ideas at the same or lower cost.
This is not a bad development. The brand, which is focused on creative innovation using AI, will ask questions like, "What can AI help us discover that we wouldn’t have found otherwise?" The brand, which focuses on cost efficiency using AI, will ask questions like "How much can we produce for less?" The first question will increase creative quality. The second question will have, when left unchecked, a levelling effect. Instead of more unique ideas, more of the same will be produced faster.
This is a trap that we can fall into when looking at the research on AI-generated advertising performance. Studies have shown that AI-optimized creatives can deliver higher click-through rates than manually designed creatives. However, this performance lift is not derived from producing more of the same thing faster; rather, it is derived from the smarter production and testing of more ideas. In other words, efficiency and effectiveness are not the same thing, and how AI creativity is being talked about by brands does not necessarily reflect reality.
What the report actually recommends
To its credit, the report doesn't just flag this shift; it offers a corrective. IAB's research points to three principles for brands trying to use AI creative responsibly and effectively:
Understand audience attitudes toward AI — particularly among Gen Z, who tend to be more attuned to (and more critical of) AI-generated content than older demographics.
Use AI to enhance creative quality, not just to produce advertising more cheaply. This is the crux of the whole report. Cost savings are real, but they shouldn't be the ceiling of what AI is asked to do.
Treat AI as a production multiplier, not a replacement for creative judgment. The brands seeing the strongest results aren't the ones removing humans from the loop but the ones using AI to test more ideas faster while still applying human judgment to what actually ships.
This lines up closely with what we're seeing across the industry more broadly. Consumer trust research shows that a significant majority of people say authentic brand engagement builds trust, and a similarly large share are willing to pay more for brands they perceive as authentic, while an even larger majority expect brands to disclose when AI is involved in their content or customer interactions. Efficiency gains mean very little if they come at the cost of that trust.
The real risk isn't using AI—it's using it without a point of view
There's a version of this shift that should genuinely concern marketers: a future where every brand in a category is running AI-generated variations of the same handful of ideas, optimized for the same engagement metrics, indistinguishable from one another except for logo and color palette. That's not a hypothetical; it's the natural endpoint of treating AI purely as a cost-cutting tool rather than a creative one.
The brands that will pull ahead over the next few years are the ones that flip the emphasis back toward the 2024 mindset, without giving up the efficiency gains of 2026. That means:
Using AI to generate a wider range of genuinely different creative directions, not just more variations of one safe idea.
Keeping humans firmly in charge of the parts of a brand's identity that carry real emotional weight, its voice, its point of view, and the moments where authenticity is non-negotiable.
Being transparent with audiences about where and how AI is involved, rather than treating disclosure as a liability to manage around.
Measuring success not just by output volume or CTR lift, but by whether the creative is actually saying something distinct.
Where this leaves brands right now
The report by the IAB confirms what we already knew: AI creative is not something for the future that we have to get ready for. The majority of advertisers are already using AI creative in their advertising. The real question for you and your team is: are you using AI in your creative process to say something better, or are you just using it to say the same thing but more cheaply?
Cost efficiency is table stakes and thus rapidly becoming a non-differentiator as AI tools, speed, and scale become available to all brands. Rather, the next competitive advantage will derive from the increasing gap between brands using AI well to express their point of view and create meaningful experiences versus those merely using AI to cut costs and retain the status quo.
The IAB report outlines the gap in AI creative adoption between good and cheap, a gap that is growing in both directions. At MyAibo, we help brands build the marketing and technical infrastructure to use AI as a genuine creative multiplier — not just a cost-cutting shortcut. If you're rethinking how AI fits into your creative pipeline, let's talk.