ChatGPT ads measured: 0.42% of responses — near the ceiling?

ChatGPT now carries paid ads. We measured how often.

Across 8,243 successful ChatGPT responses in cloro’s monitoring corpus from 2026-04-14 (the first day we saw a ChatGPT ad) through 2026-05-02, 0.42% carried at least one paid sponsored placement. That’s the headline number.

For context, here are the two paid-ad channels we can measure on Google’s AI surface today:

• Google ads on the Google SERP (the classic “Sponsored” slot, observed on AI-Overview-triggering queries): 1.05% of responses (89 of 8,439)
• Google AI Overview ads embedded inside the AI Overview block itself: 0.24% of responses (20 of 8,439)

ChatGPT’s 0.42% lands between Google’s two channels. About 4× lower than Google’s mature SERP slot, and roughly double the rate Google runs inside its own AI Overview.

The interesting read here isn’t “ChatGPT is just getting started.” It’s the opposite. ChatGPT’s ad surface may already be near its ceiling. AI-native ad placements look like they’re converging around 0.2-0.5% on both Google and OpenAI. ChatGPT could push toward Google’s classic SERP rate, but that would mean ignoring the user-tolerance pattern Google itself seems to respect on its own AI surface.

Table of contents

• The central finding: ChatGPT at 0.42%
• Two Google benchmarks, one ceiling hypothesis
• What this implies about where ChatGPT ads are going
• Who is advertising on ChatGPT today
• Methodology

The central finding: ChatGPT at 0.42%

The headline number, restated:

Channel	n (responses)	Ad-bearing	Penetration
ChatGPT ads (inside ChatGPT response)	8,243	35	0.42%

ChatGPT ads are returned in a response.result.ads[] array on the response. Each entry has a brand object (name, URL, favicon) and a cards[] array with the ad creative (image, title, body, deep-linked URL), served from bzrcdn.openai.com and tagged with utm_source=chatgpt.com&utm_medium=src. So this is unambiguously a paid placement, not an organic recommendation.

Here’s what one looks like in the wild. An SAP “AI Cloud ERP” placement rendered inline beneath the response sources:

We excluded the other commercial surfaces in ChatGPT’s response payload (inlineProducts[] for multi-merchant comparison rows, shoppingCards[] for single-merchant product cards). Those are commercial but not unambiguously paid, and bundling them in would change the question. If you’re interested in those, we wrote a separate piece on ChatGPT Shopping.

Two Google benchmarks, one ceiling hypothesis

Google’s AI surface gives us two natural benchmarks. They sit on either side of ChatGPT’s rate, and the gap between them is what I keep coming back to.

Channel	n	Ad-bearing	Penetration
Google ads (Google SERP, on AIO-triggering queries)	8,439	89	1.05%
ChatGPT ads	8,243	35	0.42%
Google AI Overview ads (inside the AI Overview block)	8,439	20	0.24%

The two Google channels are different inventories, and we treat them as such for a reason. We dug into the distinction in a separate piece on Google Ads Transparency Center vs SERP ads:

• Google ads on the SERP is the classic sponsored-search slot. Decades of advertiser demand are pre-loaded for those queries; the SERP slot just renders what the auction would have served regardless of whether AI Overview is on the page. Mature inventory, mature rate.
• Google AI Overview ads are placements woven inside the AI Overview answer itself, with redirect URLs through /aclk?.... New inventory, new placement type, much lower rate. We’ve written about extracting these embedded ads programmatically for readers who want to reproduce this measurement.

The classic sponsored slot runs about 4× more often than the in-overview placement on the same query cohort. The in-overview surface, Google’s own AI-native ad slot, comes in at 0.24%. ChatGPT’s in-response ad surface, the most direct functional analog to Google’s in-overview surface, comes in at 0.42%.

So the only two AI engines running paid ads today are converging on a similar rate. ChatGPT is slightly higher than Google, but in the same neighborhood, and roughly an order of magnitude below the mature classic-search rate.

Microsoft Copilot, Perplexity, Google AI Mode, Gemini, and Grok showed 0% paid ads across the same window. Whatever those products are pursuing for monetization, it isn’t the in-response paid ad.

What this implies about where ChatGPT ads are going

The usual read is that ChatGPT is at the start of its ad ramp and the rate will climb steeply from here. Our data fits a narrower, more interesting conclusion: ChatGPT may already be near the equilibrium rate for an AI-native ad surface.

Two things make me think so.

First, Google AI Overview has been running AI-native ads longer than ChatGPT and has Google’s full advertiser demand to draw on. It still sits at 0.24%, lower than ChatGPT’s 0.42%. If Google with all its inventory advantages has settled around 0.2-0.3% on its AI-native surface, that hints at a structural ceiling for the format, not a stage on the way somewhere higher.

Second, the classic Google SERP rate (1.05%) lives on a different page surface, on different real estate, governed by different user tolerance. Climbing from roughly 0.4% to roughly 1% inside an AI-generated response isn’t a frequency increase. It’s a different product. ChatGPT could try, but the comparable surface (Google’s in-overview slot) is the more honest signal of where this format actually lands.

The ceiling for AI-native ads probably sits somewhere in the 0.2-0.5% range that both ChatGPT and Google are already occupying. A second ad slot per response, or a more aggressive trigger threshold, could push that higher. But each step requires advertisers to tolerate sparser placement and users to tolerate denser ads in a generative answer. Neither side has obviously high tolerance.

If you’re betting on ChatGPT becoming a major ad surface, the ceiling argument is the one to falsify before the floor argument.

Who is advertising on ChatGPT today

The advertiser mix in our window is heavily B2B SaaS with a long tail of consumer brands.

ChatGPT advertisers, 19-day window (16 distinct advertisers, 35 placements):

Rippling (3), Semrush (3), HubSpot (2), CrowdStrike (2), 11x AI (2), The Wall Street Journal (2), Attio (2), Shutterstock (1), Adobe Acrobat (1), Forbes (1), McAfee (1), Lenovo (1), Top10.com (1), Biom (1), Zapier (1), Pottery Barn (1), and several other one-off placements.

One pattern worth flagging separately: AI labs are buying paid placements on Google’s AI Overview SERPs. chatgpt.com, perplexity.ai, and claude.ai all appear in the Google sponsored-search slot on AI-Overview-triggering queries during our window. Whatever the public narrative about AI engines competing with Google Search, the labs are paying Google to drive traffic from AI-Overview queries. That tells you something about where intent still lives.

The B2B-SaaS skew is partly real and partly an artifact of cloro’s prompt mix. See the methodology caveat below.

Methodology

Window. From 2026-04-14, the first day we observed paid ads[] placements on a ChatGPT response, through 2026-05-02. 19 calendar days. We anchor the window to the first ChatGPT ad observation rather than a fixed lookback because the central question is about ChatGPT specifically; the same window applies to the Google benchmarks for direct comparability. Sample sizes per channel are in the table above (8,243 ChatGPT responses, 8,439 Google AI Overview responses). Google ads on AI Overview SERPs were observable in cloro’s data starting 2026-02-10, well before ChatGPT ads, but we use the common 19-day window to keep the comparison apples-to-apples. The longer-window Google rate is statistically similar.

What “with ads” means. A response is counted as carrying paid ads if the relevant array (response.result.ads[] for ChatGPT and Google ads on AIO; response.result.aioverview.ads[] for Google AI Overview ads) is a JSON array with one or more elements. Empty arrays and missing fields are counted as zero. Penetration is ad-bearing responses divided by total SUCCESS responses, expressed as a percentage.

What we excluded. ChatGPT’s responses also carry inlineProducts[] (multi-merchant product comparison rows) and shoppingCards[] (single-merchant product cards). These are commercial but not unambiguously paid placements; including them would change the question being asked.

Country mix. The ad-bearing responses cluster heavily in the United States: 33 of 35 ChatGPT ads (94%) and 90 of 109 Google AI Overview ads (83%) were on US-locale prompts. Other countries showed isolated placements. Treat the headline rates as biased toward the US ad market; non-US rates are likely lower in this window.

Prompt-mix caveat. cloro’s customers configure the prompts, and the corpus skews toward queries about brands, comparisons, recommendations, and B2B-software topics. Commercial-intent queries surface ads more often than general queries on every search surface, so our prompt mix probably inflates the measured rates relative to a fully random sample. The advertiser mix is biased the same way: heavy B2B SaaS, a lot of AI tooling, light consumer retail. The order-of-magnitude comparison between channels is still meaningful. The specific point estimates are specific to this corpus.

If you want to track how this evolves, or where your own brand shows up across these surfaces (paid placements included), that’s what cloro’s AI visibility tracking is for. For the methodology behind the capture, the AI brand visibility tracker and AI brand visibility measurement framework walk through how it works.