The inevitability of advertising within Large Language Models (LLMs) stems from the massive $200 billion infrastructure investment that $20 subscriptions alone cannot recoup. While historical "enshittification" of platforms like Amazon and Google fuels fears of corrupted recommendations and privacy violations, a new model called agentic advertising offers a privacy-first alternative. This approach, championed through frameworks like the Ad Context Protocol (AdCP), prioritizes conversational context and themes over invasive personal data tracking and browser history. By matching ads to the user's immediate intent—such as suggesting a specific Uber ride during a travel inquiry—AI platforms can monetize trust rather than distraction. This shift poses a significant threat to traditional retail media margins as AI intercepts purchase intent early, yet it provides a critical opportunity to rebuild the digital ad economy on more ethical, helpful, and less intrusive foundations.
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