Observed Signal · Mar 2, 2026 · Funding · Source: marketecture.tv · Impact: 3/5 · Sentiment: Negative
Is AdSense for AI a Game Changer or a Flop?
Ari Paparo reviews the thesis that a new ad network could become the "AdSense for AI," prompted by start-up Koah’s recent $20.5M Series A and a blog post by Tom Tunguz. Paparo applies a "what needs to be true" framework and argues several conditions must hold for an independent AI ad network to scale: AI usage must be ad‑supported, AI ads must provide distinct, rich context, supply must be fragmented across many consumer AI apps, and independent networks must attract sufficient advertiser demand. He is skeptical about fragmentation and an independent network’s ability to reach demand at scale, noting incumbent platform advantages (Google, OpenAI, Meta) and historical precedents like AdMob’s acquisition by Google. Paparo concludes Koah and similar start-ups could achieve medium-sized exits but doubts any will become the dominant "AdSense for AI."
Discusses funding for an AI ad-network startup and analyzes whether independent ad monetization in AI can scale versus major platforms—relevant to AdTech strategy and market structure but not an industry‑shifting platform policy change.
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Key Takeaways & Evidence Grounding
- Koah announced a $20.5 million Series A round to pursue an "AdSense for AI" business model.
- Tom Tunguz published a blog post framing the thesis of an "AdSense for AI."
- Ari Paparo published an analysis in Marketecture arguing multiple conditions must be true for an independent AI ad network to scale and expressing skepticism.
- The article notes major AI/platform players (OpenAI, Google, Anthropic, Meta) could capture AI ad monetization advantages.
- The newsletter references AdMob’s historical exit to Google (reported $750 million) as a prior ad-network precedent.
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OpenAI's Ad Revolution Claims vs Product Reality
The article examines OpenAI's emerging advertising business, arguing that the company's rhetoric about an 'intelligence economy' outpaces what advertisers can actually buy today. Current ad placements run in Free and Go ChatGPT tiers as labeled sponsored cards below chat answers, available via a self-serve Ads Manager on CPM, CPC and (recently) CPA pricing. Early metrics (CTR ~0.9–2%) and falling CPMs ($60 to ~$25) suggest novelty-driven demand and limited effectiveness; minimum buy-ins have fallen from $200k to as low as $10k. OpenAI relies on third-party adtech partners (Criteo, Adobe, StackAdapt, Pacvue, Kargo, LiveRamp) and has enticed The Trade Desk's Samantha Jacobson. Competitors like Perplexity and Anthropic have largely avoided or abandoned ads. Investor projections for large future ad revenue exist, but the author is skeptical and expects a modest, mid-sized channel rather than a new third pillar of digital advertising.
Hot Spots in AI Advertising Startups
Marketecture surveys the AI-driven advertising startup landscape, arguing that AI-for-ads has evolved into several distinct approaches rather than a single universal solution. It highlights three flavors of AI-for-creatives (AI tools for designers like Flora; general ad-creation tools led by Celtra; and social-channel focus), notes Viant’s AI media-planning demo that generates a plan from a prompt, and discusses two key challenges in AI-enabled media planning: data access and agency reluctance to outsourcing. On the buy-side, the piece flags exits Scibids (acquired by DoubleVerify) and Greenbids (acquired by Perion), while naming independent players Cognitiv, Chalice, Swym, and Biddable Assets. It points to cross-channel optimization efforts from Mint.ai and Fluency (the latter’s $40M raise), and highlights sell-side activity around AdCP and AI-generated campaigns by PubMatic. Overall, the author remains cautiously optimistic about 2025–2026 for agentic, AI-powered advertising tools and ecosystems.
OpenAI Search Ads Won't Be a Big Thing
Erez Levin, Leader of Emet Advisory, presents a contrarian view on monetizing OpenAI’s search. He argues that AI search ads will not scale like traditional search advertising due to fundamental differences in user expectations for AI-generated answers and how ads fit within those results. Levin contrasts AI search with Google Search, noting that users typically want concise answers and may distrust paid rankings. He suggests that ads could only add value in discount-type scenarios and raises questions about ads within AI agents. He estimates OpenAI’s advertising revenue will be a very small share of current search ad revenue (likely under 10%, probably under 5%). The piece references Google and Perplexity, privacy trends (Apple/Safari), and the broader debate about monetizing AI-driven search.
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