A novel ad format would allow brands to sponsor access to premium features for free users. For example, McKinsey could underwrite deep research queries, or Nike could present a branded "training mode." This transforms advertising from an interruption into a value-additive, branded experience that enhances the core product.
The least intrusive way to introduce ads into LLMs is during natural pauses, such as the wait time for a "deep research" query. This interstitial model offers a clear value exchange: the user gets a powerful, free computation sponsored by an advertiser, avoiding disruption to the core interactive experience.
A custom AI tool offers more value than a generic one like ChatGPT because it can be trained on a brand's unique, paywalled intellectual property. This creates a curated experience that aligns perfectly with your teachings and provides answers that cannot be found for free on the web, solidifying your expertise.
Sourcegraph introduced an ad-supported free tier for its AMP coding agent. This strategy is not just about user acquisition; it's a research play. The ad revenue allows them to use the most advanced (and expensive) AI models and learn from a broad user base, giving them the freedom to push boundaries without being tied to specific enterprise feature requests.
Conversational ads offer an unprecedented one-on-one channel for brands to interact with customers at scale. The resulting data—customer questions, complaints, and feedback—is a goldmine for product development and other business functions, potentially exceeding the value of immediate customer acquisition.
The ChatGPT app's blank start screen represented wasted real estate. The "Pulse" feature transforms this into a personalized feed based on user history. This creates a highly valuable, monetizable surface for ads placed *between* prompts, avoiding the conflict of serving ads within direct AI responses.
Unlike competitors who would struggle to introduce ads into AI chat, Meta's user base is already accustomed to ads in their feeds. This gives Meta a unique advantage to monetize a proactive consumer AI agent that can surface sponsored suggestions for shopping or travel without creating user friction.
Generative AI changes brand discovery from a budget-driven game to one based on relevance, credibility, and usefulness. This levels the playing field, allowing smaller, more agile brands to compete with larger incumbents who traditionally relied on massive ad budgets.
Instead of traditional cost-per-click models, ChatGPT could pioneer a "verified outcome" system where advertisers pay only upon a completed transaction and user satisfaction. This would inherently favor advertisers with superior products that lead to actual conversions, improving ad quality and relevance for all users.
The goal for advertising in AI shouldn't just be to avoid disruption. The aim is to create ads so valuable and helpful that users would prefer the experience *with* the ads. This shifts the focus from simple relevance to actively enhancing the user's task or solving their immediate problem.
OpenAI's Agent Builder could establish a middle market between free, ad-supported consumers and large enterprise API users. This "prosumer" tier would consist of power users willing to pay based on their consumption of advanced, automated workflows, creating a new revenue stream.