The news: ChatGPT ads are taking shape as OpenAI lines up agencies and firms up its ad model plans ahead of a possible February launch.

• OpenAI is onboarding “dozens of advertisers” and asking for spending commitments of under $1 million, per The Information.
• Early terms of service for brands indicate ads will be priced based on views rather than clicks, and no self-serve buying tools are available yet.

What it means: OpenAI’s view-based pricing model contrasts with the operations of most search-style platforms, including Google and Amazon. Its CPM model may reflect a lack of confidence in click-through rates, reinforcing the idea that chatbot ads provide exposure and influence rather than direct-response intent capture.

This approach reflects how AI chat environments differ markedly from search engines and ecommerce marketplaces where clicks and conversions are central. Measuring ad efficacy will be more complex in a chatbot interface that lacks clear page views or search clicks.

Still, the move introduces tension between privacy commitments and the potential benefits of contextual targeting. While OpenAI states that ads won’t influence ChatGPT’s answers and that it won’t sell conversation data to advertisers, the platform could still use personal signals to match relevant ads. That could introduce user privacy concerns around how data is interpreted and applied.

Why it matters: This suggests ads in large language model (LLM) experiences might require new metrics for attention, relevance, and conversion, especially in situations where users are asking for help rather than searching.

Google DeepMind CEO Demis Hassabis called it surprising that OpenAI is introducing ads “so early,” per Axios. OpenAI is expected to accrue about $143 billion in negative cumulative free cash flow between 2024 and 2029, raising the stakes for it to diversify revenues to cover AI’s development and compute costs.

Recommendations for marketers: OpenAI’s model offers a preview of how LLM marketing could evolve—intent-led and measured more by ad relevance than by clicks. Agencies should keep a close eye on how OpenAI’s ad model evolves and prepare for experimentation.

• Shift planning from placement-first thinking to recommendation-first, asking not just where ads run, but why an AI system would credibly surface the brand in the first place.
• Design context-aware campaigns that map specific products and messages to clear user intents, recognizing that relevance in conversational environments is driven by what users are asking for in the moment.
• Closely monitor how view-based pricing is defined, counted, and optimized within ChatGPT to understand what constitutes meaningful exposure in a chat-based experience.
• Treat organic visibility in AI assistants as foundational, not optional.

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