VAB puts US programmatic spend on AI slop at up to $978.7m.

The Video Advertising Bureau, the US television industry's marketing body, estimates that between $530.1m and $978.7m of US open-web programmatic spend goes on AI slop. It comes from a 25-page members' deck reported by PPC Land on 28 October.
The estimate is VAB's own arithmetic. It takes the ANA's finding that AI slop made up 1.3% to 2.4% of open-web programmatic spend in the first quarter of 2026 and applies it to eMarketer's $40.78bn projection for 2025 US programmatic display spending. The deck adds 11 more borrowed statistics, including Thales data putting bad bots at 40% of 2025 web traffic and FTC figures showing $2.1bn of US losses to scams that started on social media in 2025.
The underlying ANA study, run with TAG and Fiducia, found that slop inventory was graded premium more than 70% of the time and performed close to or better than clean supply on invalid traffic and viewability, which is why it is hard to filter out. Those findings are not in VAB's deck.
PPC Land's check of the deck found three figures that do not match their sources. A $1.2bn Meta share of social media scam losses leaves out Instagram's $234m. A $4.6bn cost of fake influencer followers does not follow from the method given, which would produce about $8.9bn. And FTC shares of loss reports by age are labelled as shares of dollars. The deck is undated, contains no new research, and comes from a body that sells TV against digital platforms.
The slop problem is not limited to the US. Gulf advertisers buying open-web programmatic in English and Arabic face the same risk, and nothing in the ANA's definition limits slop to English-language sites. The sensible response is to ask verification partners for page-level reporting on AI-generated content rather than relying on domain blocklists or quality grades alone.
Why it matters
Low-effort AI sites can grade as premium inventory, so buyers need page-level checks, not domain lists, to keep budgets away from them.
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