Analyst Eric Sufert predicts OpenAI's ad model will not be anchored to the content of a user's query, which could compromise trust in the answer's objectivity. Instead, it will function like Instagram's feed, where ads are targeted based on a user's broader conversion history, independent of the immediate conversational context.

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OpenAI faced significant user backlash for testing app suggestions that looked like ads in its paid ChatGPT Pro plan. This reaction shows that users of premium AI tools expect an ad-free, utility-focused experience. Violating this expectation, even unintentionally, risks alienating the core user base and damaging brand trust.

According to Ben Thompson's Aggregation Theory, OpenAI's real moat is its 800 million users, not its technology. By monetizing only through subscriptions instead of ads, OpenAI fails to maximize user engagement and data capture, leaving the door open for Google's resource-heavy, ad-native approach to win.

While competitors focus on subscription models for their AI tools, Google's primary strategy is to leverage its core advertising business. By integrating sponsored results into its AI-powered search summaries, Google is the first to turn on an ad-based revenue model for generative AI at scale, posing a significant threat to subscription-reliant players like OpenAI.

While other AI companies are hesitant, Google is expected to lead LLM ad integration. As a company built on ads, it is culturally positioned to implement monetization quickly and effectively, unlike competitors that may view ads as a necessary evil rather than a core competency.

OpenAI has a strategic conflict: its public narrative aligns with Apple's model of selling a high-value tool directly to users. However, its internal metrics and push for engagement suggest a pivot towards Meta's attention-based model to justify its massive valuation and compute costs.

Previously, marketers told Meta who to target. With the new AI algorithm, marketers provide diverse creative, and the AI uses that creative to find the right audience. Targeting control has shifted from human to machine, fundamentally changing how ads are built and optimized.

Ben Thompson's analysis suggests OpenAI is in a precarious position. By aggregating massive user demand but avoiding the optimal aggregator business model (advertising), it weakens its defense against Google, which can leverage its immense, ad-funded structural advantages in compute, data, and R&D to overwhelm OpenAI.

As competitors like Google's Gemini close the quality gap with ChatGPT, OpenAI loses its unique product advantage. This commoditization will force them to adopt advertising sooner than planned to sustain their massive operational costs and offer a competitive free product, despite claims of pausing such efforts.

The long-term monetization model for consumer LLMs is unlikely to be paid subscriptions. Instead, the market will probably shift toward free, ad- and commerce-supported models. OpenAI's challenge is to build these complex new revenue streams before its current subscription growth inevitably slows.

For an AI chatbot to successfully monetize with ads, it must never integrate paid placements directly into its objective answers. Crossing this 'bright red line' would destroy consumer trust, as users would question whether they are receiving the most relevant information or simply the information from the highest bidder.

OpenAI Ads Will Mirror Instagram's User-History Targeting, Not Google's Contextual Search | RiffOn