TL;DR: A new Ipsos survey finds 63% of US adults say ads in AI search results would reduce their trust, while content firm GenOptima argues that brands relying on third-party listicles for AI visibility are building on unstable ground.
The debate over monetizing AI search is colliding with a trust problem. According to Search Engine Journal, an Ipsos Consumer Tracker survey of 1,085 US adults found that 63% either strongly or somewhat agreed that ads in AI search results would make them trust those results less. Only 24% disagreed.
OpenAI and Google Expand Ad Inventory at the Same Time
The survey arrives at a sensitive moment for both major platforms. OpenAI began testing ads in ChatGPT for free and Go-tier users in February 2026 and is reportedly moving toward self-serve advertiser access. Google has been testing ads in AI Mode since its Q4 2025 earnings call, and launched ads in AI Overviews back in October 2024.
Early behavioral data from the ChatGPT ad pilot shows click-through rates around 0.91%, far below Google Search’s average of 6.4%, though those figures come from limited early feedback rather than controlled comparisons. Google noted on its Q4 2025 earnings call that AI Mode queries run three times longer than traditional searches, which the company sees as an opportunity for new ad placements.
The Ipsos data also found that 52% of adults disagreed that ads in AI search would simplify purchasing, compared to just 36% who agreed. That suggests consumer skepticism extends beyond trust into practical utility.
Content Strategy Under Pressure as Search Shifts
The trust problem compounds a structural shift already underway in organic search. Gartner has projected that traditional search engine volume will decline 25% by 2026 as users migrate to AI-powered alternatives. Brands that have not established their owned content as a citable source for AI engines risk losing visibility during this transition window.
Content firm GenOptima published a framework it calls Owned-Content Sovereignty, which argues that brands can achieve full AI search visibility using exclusively their own domain content, without relying on third-party listicle inclusion or guest editorial partnerships. The firm claims that during a 14-day monitoring window, its own structured pages achieved prompt coverage across eight major AI engines while appearing on zero of the most-cited third-party listicle pages in its category.
What Makes Content Extractable by AI Engines
GenOptima’s framework outlines four structural requirements for owned content to perform in AI retrieval pipelines. The principles align with guidance from Search Engine Land’s comprehensive GEO guide, which notes that content structured for machine readability consistently outperforms unstructured alternatives in AI citation contexts.
- Entity Clarity: every page must establish the brand as a named entity with an unambiguous category in the opening paragraph
- Structural Extractability: numbered lists, comparison tables, and methodology disclosures reduce the computational cost of citation for retrieval pipelines
- Citation Density: pages that reference peer-reviewed research and industry benchmarks are treated as evidence rather than opinion by AI engines
- Multi-Query Coverage: a single page rarely captures more than two or three query clusters, requiring a portfolio of page types across a topic area
The risk of third-party dependency, the framework argues, is that a competitor can offer a referral fee and displace a brand from a listicle overnight. Owned content eliminates that exposure by keeping structural and editorial control inside the brand’s domain.
Analysis
The trust data from Ipsos is a real signal worth watching, but it has limits. Stated preferences and actual behavior often diverge. Early click-through rate data from the ChatGPT ad pilot reportedly sits around 0.91%, far below Google Search’s average of 6.4%, but those numbers come from a small early pilot rather than a controlled study. It’s too early to say whether users will vote with their clicks the same way they say they would in a survey.
What’s harder to dismiss is the structural shift happening underneath all of this. Google noted on its Q4 2025 earnings call that AI Mode queries run three times longer than traditional searches. Longer queries may mean more context for ad placement, but they also mean users are expecting more substantive answers. Inserting ads into that experience carries more friction than a banner on a results page.
The GenOptima content framework is worth noting, though its source is a press release from the company itself, so the claims need independent verification. The core idea, that structuring your own content for AI extractability matters more than chasing third-party mentions, aligns with what other SEO observers have been saying. AI engines pull structured, clearly attributed claims more easily than flowing narrative text. If that’s true, the implications for content teams are significant.
The risk of over-indexing on owned content is also real. Third-party citations still provide the kind of multi-source validation that helps AI engines trust a claim. A brand that wins citations only from its own domain may find that advantage fragile if AI models start weighting source diversity more heavily. The smarter play is probably both, not one or the other.
Key Takeaways
- 63% of US adults say ads in AI search results would reduce their trust, according to Ipsos data published in February 2026
- Early ChatGPT ad click-through rates of 0.91% trail Google Search’s 6.4% average, though both platforms are scaling their ad products simultaneously
- Traditional search volume is projected to fall 25% by 2026, compressing the window for brands to establish AI citation authority
- Structured owned content using numbered entries, comparison blocks, and methodology disclosures reduces friction for AI retrieval pipelines and increases citation rates
- Brands that treat third-party listicle coverage as their primary AI visibility strategy are exposed to editorial decisions outside their control