Koah, an advertising platform built for generative AI applications, reported that its gross merchandise value (GMV) increased fourfold in the third quarter of 2026 compared with the second quarter, as brands explore advertising within AI-powered conversations.
The company’s latest update points to growing commercial activity in an emerging advertising channel where consumers use AI tools to research products, compare options and seek personalized recommendations. Koah connects advertisers with AI applications through contextual ad formats designed to fit into conversational experiences rather than traditional search results or display placements. World Advertising Report+1
The reported GMV increase is a company-reported growth indicator, not a disclosure of advertising revenue, profitability or advertiser return on investment. Koah has not provided an absolute GMV figure in the announcement, making it difficult to assess the size of the business or compare its growth with established advertising platforms.
The shift nevertheless reflects a broader industry question: how will advertising work when consumers increasingly explain their needs in natural language and ask AI systems to help narrow their choices?
Conversational advertising offers a different context
Traditional search advertising often matches an ad to a query, while display advertising can rely on audience segments, browsing behavior or page context. In conversational AI, a user may describe a situation, preferences and constraints over several exchanges. That context could give advertisers new ways to match messages to consumer intent.
Koah’s platform is designed to place native advertising within AI-powered applications. Its Card format is intended to integrate a brand message into the user experience. The company reports a 1.96% click-through rate for the format, which it says is roughly 40 times the average for display ads. That comparison should be treated as a company claim: the announcement does not disclose the underlying sample size, campaign mix, measurement period or display benchmark used. World Advertising Report
The opportunity is not simply to transfer search advertising into chat interfaces. An AI conversation may help a user explore a category or evaluate options before the person is ready to purchase. In an interview with industry publication Tipsheet, Koah CEO Nic Baird described conversational AI as a potential consideration channel and identified attribution and targeting as areas still developing. tipsheet.ai
For advertisers, that creates an early testing opportunity, but also a measurement challenge: a click may indicate interest without proving that the placement changed a decision or generated incremental sales.
Advertisers are testing the channel
UrbanStems vice president of growth Kristin Secora-Sampat said the company explored Koah because it wanted to understand the channel before broader adoption. Her comments, included in Koah’s announcement, reflect a familiar early-market strategy: test new consumer touchpoints while budgets and measurement practices are still taking shape.
Koah also reports differences in prompt patterns across its network compared with reference data for ChatGPT. Information-seeking prompts accounted for 41% of prompts on Koah’s network, compared with 24% in the reference data. Writing accounted for 3%, versus 24%, while practical guidance represented 9%, compared with 29%.
These figures suggest that prompt behavior can vary across AI environments. However, the announcement does not fully describe the reference dataset, sampling method or classification rules, so the percentages should not be interpreted as a representative comparison of all AI users.
The company also says daily queries containing “gift” or “gifts” have more than doubled since the first week of August, with recent volumes approaching three times the early-August baseline. That could be useful for identifying seasonal product-discovery activity within its network, but it does not establish a market-wide trend.
Monetization must balance relevance and trust
AI application developers face a business-model challenge as they scale products that require computing resources to serve user requests. Advertising offers one potential revenue stream, and Koah is building infrastructure that connects these applications with brands seeking contextual placements.
But conversational advertising also raises questions about transparency. Ads appearing alongside AI-generated answers need to be distinguishable from organic recommendations, particularly when users rely on assistants to compare products or make decisions. The U.S. Federal Trade Commission’s native-advertising guidance emphasizes that commercial disclosures should be clear and understandable to consumers. The IAB’s AI Transparency and Disclosure Framework also provides guidance on transparency in consumer-facing AI experiences. Federal Trade Commission+1
For Koah, long-term adoption will depend on more than GMV growth or click-through rates. Advertisers will need evidence about conversion quality, incrementality, brand safety and the effect of placements on user experience. AI application developers, meanwhile, must ensure monetization does not undermine consumer trust.
Koah’s reported growth offers an early signal that brands are allocating money to conversational AI experiments. Whether the channel becomes a durable part of media plans will depend on independently assessable performance, transparent ad presentation and the ability to scale across diverse AI applications.
Market Landscape
Conversational advertising is emerging as AI applications expand beyond question answering into product research and decision support. Ad platforms such as Koah are trying to establish a monetization layer for these environments, while advertisers investigate how to reach users through intent-rich interactions. tipsheet.ai+1
The category remains immature. Measurement standards, attribution models, ad formats and disclosure practices are still evolving. Industry guidance from the IAB and FTC offers a starting point for transparency, but it does not resolve the commercial challenge of determining whether a conversational placement generates incremental value.
Strategic Outlook
Koah’s fourfold quarterly GMV increase suggests accelerating activity on its network, but the absence of absolute figures and independently validated campaign results limits what can be concluded about its scale.
The next indicators to watch are repeat advertiser spending, publisher and application adoption, conversion and incrementality data, and consistent disclosure of sponsored content. If conversational advertising can demonstrate measurable value without compromising the usefulness or trustworthiness of AI interactions, it may become a distinct channel within digital media planning.
Top Insights
- GMV increased fourfold: Koah reported Q3 2026 GMV was four times its Q2 level, without disclosing absolute volume.
- A new advertising context: The platform places native ads within generative AI applications, where users may describe detailed needs and preferences.
- Performance claims need context: Koah’s reported 1.96% Card-format click rate and display comparison lack published benchmark methodology in the announcement.
- Prompt patterns differ: Koah reports variation in information-seeking, writing and practical-guidance prompts across its network and reference data.
- Transparency is essential: Clear distinctions between advertising and organic AI recommendations will be important for user trust.
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