CEO Brian Chesky sees advertising as a multi-billion dollar opportunity but is intentionally holding off. Instead of replicating Google's legacy search ad model, he wants to first perfect an AI-driven search experience and then design a new advertising unit tailored for that conversational interface, ensuring it doesn't degrade user trust.
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As users increasingly interact with voice-first AI assistants, the traditional digital advertising model faces a major disruption. With no screen to display ads, companies that rely on visual ad revenue, like Google, must find new ways to monetize these interactions without ruining the user experience.
Airbnb's CEO argues that access to powerful AI models will be commoditized, much like electricity. Frontier models are available via API, and slightly older open-source versions are nearly as good for most consumer use cases. The long-term competitive advantage lies in the application, not the underlying model.
Chesky observes that the vast majority of AI startups focus on enterprise applications, leaving a significant opportunity in consumer-facing products. He argues that the largest companies will be those that impact daily life and advises entrepreneurs not to shy away from the harder, "hits-driven" consumer market.
Unlike competitors embracing AI, Airbnb is intentionally avoiding integration with generative AI trip planners like ChatGPT. The company is making a high-risk bet that its brand is strong enough to retain direct bookings, rather than becoming a background "data layer" in a user journey that starts on another platform.
Instead of starting with simple generative AI tasks, Airbnb focused on the most difficult application: resolving urgent customer issues like lockouts. This high-stakes approach allowed them to build a robust agent that can now be applied to less critical, "up-funnel" use cases like travel planning.
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.
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.
Brian Chesky compares the current state of AI interfaces to the MS-DOS era—a functional but primitive way to interact with powerful new technology. He believes the chatbot is not the final form and a "multi-touch" moment is needed, where devices and apps are completely re-imagined for an AI-native consumer world.
Unlike Google's ad-based model, future AI platforms like ChatGPT may vertically integrate and fulfill user requests directly. Instead of sending traffic to a real estate agent, the AI might become the real estate agent, capturing the entire value chain and eliminating the need for third-party businesses.
Brian Chesky applies the classic "overestimate in a year, underestimate in a decade" framework to AI. He argues that despite hype, daily life hasn't changed much yet. The true shift will occur in 3-5 years, once the top 50 consumer apps are rebuilt as AI-native products.