Nearly two-thirds of digital video buyers now use generative AI for creative, according to IAB’s latest report. That is the story behind the headline in practical terms, and it is a jump from the half of advertisers reported a year earlier. If your budget still treats AI as a side experiment, your competitors are already pricing production differently.
What the number actually says
Precision matters here, because this stat gets rounded in every direction. TV News Check’s coverage of the IAB full report says almost two-thirds of buyers now use GenAI for digital video creative, up from half in 2025. It also says one-third of ad assets are expected to include GenAI this year, up from one-quarter in 2025, with a projection of 43% by 2027.
So “almost two-thirds” is the safe wording, and rounding it to a tidy figure adds precision the survey does not claim. It is not a census of the industry. It is a survey of buyers, and it measures use, not dependence. A team that generated one storyboard with an AI tool counts the same as a team producing hundreds of variants a week.
Two-thirds of buyers use GenAI, but only about one-third of ad assets include it. Adoption is wide. Depth is still shallow, and that gap is where your budget decision lives.
Why this matters for creator and influencer budgets
The money is large. IAB’s Part One release projects U.S. digital video ad spending will surpass $80B in 2026, growing 11% year over year. Creative is the cost line most exposed to automation inside that total.
For influencer programs, the pressure lands in three places:
- Paid amplification assets. Cutdowns, resizes, captions, and hook variants of creator content are the first candidates for AI production.
- Concept testing. Cheap synthetic drafts let you screen ideas before paying a creator for the full shoot.
- Synthetic creators. Fully generated “UGC” competes directly with human creator fees, and it carries real disclosure risk.
The honest question is not “can AI replace creators?” It is which part of the production chain you are paying a human premium for, and whether that premium still buys something.
The savings are real. So are the hidden costs.
Vendors pitch speed. Finance teams hear “lower creative spend.” Both skip the review layer. Every AI-assisted asset still needs brand checks, legal review, rights clearance, and often a reshoot when something looks off. We unpacked this in our look at rework costs, and the pattern holds: time saved in generation often reappears in approvals.
Photorealism is its own trap. Synthetic video that almost passes as a real person invites audience backlash and platform scrutiny, which is why a photorealism vetting protocol belongs before any scaled launch. Rights are the other landmine. If you remix creator footage into dozens of variants, check your contracts first, using the approach in our guide to content atomization rights checks.
Large spenders and small ones are not in the same boat
A useful finding for mid-market teams: buyers are not asking AI to run unsupervised. In the same IAB report, 40% of buyers want humans in the loop on agentic AI, and 50% of small and medium spenders say human oversight is important. Buyers also want audit trails for explainability (36%) and guardrails to limit agent actions (31%).
That tracks with what we see in practice. Oversight is not a brake on adoption. It is the condition for it. A risk-tiered approval model lets low-risk assets (resizes, captions) move fast while anything with a synthetic face or a health claim gets a human sign-off.
A budget reset in four moves
- Baseline your current cost per finished asset. Include revisions, approvals, and legal time, not just production invoices. Without this, “AI savings” is a guess.
- Split the line by task. Separate ideation, versioning, and hero content. Put AI against versioning first, where risk is lowest.
- Fund governance explicitly. Set aside budget for review capacity and tooling. Our piece on brand guardrails for AI pipelines outlines what to vet before scaling.
- Hold back a creator premium. Keep human creators for content where trust, personality, and authenticity drive results, and test AI variants against them with a control.
Notice the order. Measurement comes before reallocation. If an AI variant wins on click-through but loses on downstream sales, you want to know before you cut the creator line.
Disclosure is a budget item too
Synthetic content that mimics a customer testimonial raises disclosure questions that no creative team should answer alone. Build the legal review into your timeline and your cost model. Our checklist on AI UGC rights and disclosure is a reasonable starting point for your brief template.
For a sense of how quickly the baseline is moving, the 2025 IAB release reported that half of advertisers were already using Gen AI to build video ads. One year later, it is nearly two-thirds. Expect the next budget cycle to start from a higher floor.
FAQs
Is it true that most video buyers use generative AI?
It is close. IAB’s 2026 full report, as covered by TV News Check, describes almost two-thirds of buyers using GenAI for digital video creative. Cite IAB’s original wording of almost two-thirds when you present it internally, rather than a rounded figure.
Does this mean creative budgets should shrink?
Not automatically. AI can cut versioning and testing costs, but review, rights clearance, and rework add cost back. Baseline your real cost per finished asset before you claim savings.
Should brands replace human creators with AI-generated UGC?
Be cautious. Synthetic testimonials carry disclosure, rights, and audience-trust risks. Use AI for versioning and concept testing first, and test synthetic content against human creator content before shifting spend.
What share of video ads will use generative AI?
Per TV News Check’s report on the IAB findings, one-third of ad assets are expected to include GenAI this year, up from one-quarter in 2025, with a projection of 43% by 2027.
How much human oversight do buyers want?
Forty percent of buyers want humans in the loop on agentic AI, and 50% of small and medium spenders say human oversight is important. Audit trails and guardrails are also in demand.
Where should a mid-size brand start?
Start with low-risk, high-volume tasks such as resizing, captioning, and hook variants. Add a tiered approval process, then expand to higher-risk formats only after a controlled test shows no loss in performance.
This week, pull your last ten creator-derived paid assets and calculate the full cost of each, including review and revisions. That number is your baseline for deciding where AI earns budget and where human creators still do.
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