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Blog›Guides›AI Campaign Visual Statistics: 15 Numbers Agencies Can't Ignore [2026]

AI Campaign Visual Statistics: 15 Numbers Agencies Can't Ignore [2026]

Filippo PietrantonioOctober 9, 20267 min read
Guides

Eighty-three percent of advertising executives now say their company uses AI in creative, up from 60% two years earlier (IAB, January 2026). But only 45% of consumers feel positive about AI-made ads, while 82% of those same executives think consumers do. That 37-point gap is the real story of AI campaign visuals in 2026: adoption is close to settled, and execution is where agencies win or lose.

If you run a creative agency, a design studio, an e-commerce brand or a fashion label, this roundup is meant to be the reference you can quote in a pitch deck, a client brief or an internal budget meeting. We collected 15 numbers, checked each one against the live source page, and added what it means in practice.

A note on method: where a figure comes from a vendor-run survey or a vendor's own cost illustration, we say so. Where outlets disagree on a number, we use the primary source. For the bigger picture behind these numbers, see our deep dives on what AI-generated advertising means for agencies and how AI is reshaping the creative services industry.

Table of Contents

How Widely Is AI Used in Creative Work?

Most creative teams now use AI in production. IAB's 2026 survey found 83% of ad executives say their company uses AI in creative, and a September 2026 survey of 760 creative professionals found 81% have already released AI-made content. The question has moved from "whether" to "how well."

1. 83% of ad executives say their company uses AI in creative, up from 60% in 2024. This comes from IAB's "The AI Ad Gap Widens," based on 104 U.S. ad executives surveyed between October 2025 and January 2026. By channel, advertisers reported AI use of 85% in social media and 73% in display (IAB). Social and display are exactly where campaign visuals get produced in volume.

2. 81% of creative professionals have released content made with AI. Luma Labs, an AI company, surveyed 760 creative professionals across agencies, brands, production companies and freelancers. Treat it as a vendor-run survey, but the sample is specific and the direction matches IAB's.

3. 42% of those creatives use AI for image generation. In the same Luma Labs survey, image generation sits well ahead of video editing assistance, which came in at 38%. Stills are the most common entry point, which is why consistency across a set of stills is the bottleneck worth solving first.

4. More than 35% of fashion executives already use generative AI. McKinsey's State of Fashion 2026 reports that more than 35 percent of executives use generative AI in functions such as online customer service, image creation, copywriting, consumer search and product discovery. Some secondary outlets quote a higher figure for the same report. We use the number printed on McKinsey's own page.

Why Cost Efficiency Is Driving Adoption

Cost is the top reason advertisers cite for using AI. In IAB's 2026 survey, 64% named cost efficiency as the leading benefit, up from fifth place in 2024. Traditional photography is expensive enough that even partial substitution changes a production budget.

5. 64% of advertisers name cost efficiency as the top benefit of AI. In 2024 it ranked fifth. Creative innovation, the 2024 leader, slipped to 61% from 64% (IAB). The motive has shifted from novelty to economics.

6. Traditional product photography runs $50–$350 per finished image. That is Shopify's 2026 planning range, as reported in Nightjar's cost breakdown (updated September 2026). Shopify's range for a photographer's day is $500–$3,000, and rush fees run from 25% to 200% of job cost.

For comparison, Nightjar illustrates an AI workflow at $2.56 per approved image. That example assumes 120 completed shots, 80 approved images and $30 per hour of labor, and Nightjar labels these as planning inputs rather than market rates. Read it as a vendor's illustration of the order of magnitude, not a benchmark. We walk through the full math in how to cut fashion campaign production costs with AI and how to replace a product photography studio with AI.

What Do Consumers Actually Think of AI Ads?

Consumers notice AI ads and are less enthusiastic than advertisers assume. IAB found 71% of consumers believe they have seen an AI-created ad, but only 45% feel positive about them. Executives estimated 82%. Ignoring that gap is the most expensive mistake in the data.

7. 71% of consumers believe they have seen an AI-created ad, up from 54% in 2024. The consumer sample was 505 U.S. Gen Z and Millennial adults who engaged with ads (IAB). Audiences are not naive. They are looking.

8. 82% of executives think consumers feel positive about AI ads. 45% actually do. IAB puts the gap at 37 points, up from 32 in 2024. If your pitch to a client assumes the audience is as comfortable with AI as your team is, this number is the counterweight.

9. 39% of Gen Z consumers feel negative about AI ads, up from 21% in 2024. Among Millennials the figure is 20%, up from 15% (IAB). Gen Z is also more likely to call AI-using brands "inauthentic": 30% versus 13% of Millennials.

What this means in practice: the audience is not rejecting AI imagery, it is rejecting imagery that looks generic, disconnected or careless. A campaign where every frame shares lighting, styling and world reads as a deliberate shoot. A grab bag of one-offs reads as filler. That is the argument in why visual brand consistency is becoming a competitive moat and in 5 reasons AI visuals don't look like a campaign.

The Disclosure Question

Most advertisers disclose AI use at least sometimes, but few do it consistently. IAB found 89% disclose at least sometimes, while fewer than half always do. Disclosure is becoming a standing part of client scopes.

10. 89% of advertisers disclose AI use at least sometimes, but fewer than half always do. IAB reports that figure is essentially unchanged from 2024 (IAB). Separately, 73% of consumers said knowing an ad used AI would increase or not change their likelihood to purchase. Disclosure, in other words, looks far less risky than avoiding it and being found out.

If you work with clients on AI visuals, write the disclosure rule into the statement of work before the first asset ships. Our step-by-step guide to adding AI visuals to an agency workflow covers contract language, QA and sign-off.

Visual Quality and Product Pages

The numbers on e-commerce image quality show the problem AI is being asked to solve. Baymard's 2026 benchmark found up to 62% of leading sites rate "mediocre" or worse on product page UX, and large shares still miss basic image types like in-scale shots and human-model shots.

These three figures come from Baymard Institute's product page benchmark (updated March 2026, 155+ benchmarked sites):

11. Up to 62% of leading ecommerce sites have a "mediocre" or worse product page UX. Only 48% of leading U.S. and European desktop sites rate "decent" or better, and mobile is lower at 38%.

12. 37% of sites don't provide "In Scale" images. Baymard also reports 42% of users try to judge a product's size from the page images. A missing in-scale shot is a missing answer to a question shoppers are actively asking.

13. 23% of sites don't provide a "Human Model" image. For fashion and accessories, that is a conversion gap you can close with a consistent set of on-model visuals rather than a second shoot.

Here is the nuance. These are gaps in image coverage, not proof that AI images convert better. AI helps because it makes covering every angle, scale and context cheap enough to actually do it, provided the set looks coherent. A page with five mismatched AI images can perform worse than two good photographs. See what campaign visual consistency means and how to build a scalable visual content system for e-commerce.

What Is Changing Inside Agencies

Agencies are adopting faster than they are governing. In the Luma Labs survey, 52% of organizations have no structured, enforced process for approving AI tools, and creatives expect AI to push agency fees and client spending in different directions.

14. 52% of organizations have no structured, enforced process for evaluating or approving AI tools. About one in three said adoption is driven by individual employees experimenting on their own (Luma Labs). Tool sprawl is the hidden cost: agencies in the sample evaluated 6.5 tools and dropped 3.5 over twelve months.

15. 55% of agency creatives expect their fees to rise because of AI, while 53% of brand-side creatives expect to cut agency spend. Same survey, same caveat about vendor-run research. The two expectations point in opposite directions, which makes pricing conversations the next friction point. Agencies that price on outcomes and consistency, not hours saved, are better positioned.

This is also where a campaign-first tool earns its place. Rainfrog was built inside a working design agency to solve the consistency problem: you combine products, characters, styles and environments instead of writing prompts, so the whole set looks like one shoot. You can see how that works without prompts and what the workflows look like.

How to Use These Statistics in Your Own Planning

Use the numbers to set expectations, not to justify decisions you have already made. Three practical steps cover most agencies and brands.

  1. Pick your claim by audience. For a CFO, lead with the cost figures (stats 5 and 6). For a brand director, lead with the consumer gap (stats 7 to 9).
  2. Write a disclosure and QA policy first. Decide who approves AI assets and when you label them, using stat 10 as your benchmark for what peers do.
  3. Measure consistency, not volume. Track how many assets in a set pass a brand-coherence check, not how many images you generated. Our complete guide to AI marketing visuals and the real cost of inconsistent brand imagery cover how.

If you are weighing whether your team is ready, 6 signs your agency needs an AI visual production tool is a quick diagnostic, and the end of the campaign photoshoot covers what changes for fashion production specifically.

Frequently Asked Questions

What percentage of agencies use AI for campaign creative?

IAB's 2026 survey found 83% of ad executives say their company uses AI in creative, up from 60% in 2024. A separate September 2026 Luma Labs survey of 760 creative professionals found 81% have released AI-made content. Both are survey results, so exact shares vary with the sample.

Do consumers dislike AI-generated ads?

Not uniformly. IAB found 45% of consumers feel positive about AI ads, and negative sentiment is concentrated among Gen Z at 39%, versus 20% for Millennials. Executives overestimated positive sentiment at 82%. Quality and authenticity appear to matter more than the label itself.

How much does traditional product photography cost compared with AI?

Shopify's 2026 planning range, as reported by Nightjar, is $50–$350 per finished image and $500–$3,000 per photographer day. AI per-image costs depend on the tool, plan and approval rate, so build your own estimate from approved images rather than generated ones.

Should we tell clients and audiences when we use AI visuals?

Most advertisers already do at least sometimes (89% per IAB), and 73% of surveyed consumers said knowing about AI use would increase or not change their purchase likelihood. Put the rule in the statement of work. Requirements also vary by market and platform, so check current rules for your regions.

Are these statistics reliable enough to cite?

The IAB, Baymard and McKinsey figures come from named research programs with published methods. The Luma Labs figures come from a vendor-run survey and the Nightjar cost example is a vendor illustration, so cite them as such.

Key Takeaways

  • AI in creative is mainstream: 83% of ad executives report using it (IAB), and 81% of surveyed creatives have released AI-made content (Luma Labs).
  • Cost efficiency is now the top reason advertisers cite, at 64%.
  • Consumers notice: 71% believe they have seen an AI ad, and only 45% feel positive about them.
  • Gen Z is the most skeptical group, at 39% negative, so authenticity and coherence matter.
  • Image coverage gaps are common on e-commerce sites, which is where consistent AI visuals help most.
  • Governance lags adoption: 52% of organizations have no structured approval process for AI tools.

Want campaign visuals that read as one shoot rather than a pile of one-offs? Explore Rainfrog or see pricing.