Unlike traditional search which serves links, AI "answer engines" provide opinions and summaries. This creates a new marketing vector: sentiment. Brands must now track not just if they are mentioned, but *how* they are described, and analyze why that sentiment changes over time.

While familiar metrics like ROAS and CPC will persist, AI search advertising requires a new approach. Instead of focusing on discrete keywords, advertisers must broaden their strategy to target entire conversational contexts and semantic categories to capture richer user intent.

Unlike search ads that target keywords, ChatGPT ads will target a user's intent inferred from a conversation. The system essentially qualifies the user's needs *before* showing an ad, resulting in traffic that is already in a buying mindset and more likely to convert.

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.

Instead of relying on user data or cookies, Large Language Models (LLMs) can analyze the content of publisher web pages to infer purchase intent. This allows marketers to target audiences based on the context of what they are reading, a fully privacy-compliant approach.

With the rise of AI-driven agent search, consumers use conversational prompts ('What should I pack for Greece?') instead of simple keywords. To appear in these results, brands must shift from keyword optimization to tracking data on sources, sentiment, and contextual relevance to avoid becoming invisible.

As privacy regulations and browser changes erode deterministic signals like cookies, advertisers must shift to predictive models. AI-driven analysis of contextual signals provides a scalable and future-proof way to reach relevant audiences without relying on shrinking pools of user-level tracking data.

OpenAI plans to personalize ads not just on immediate queries but by analyzing a user's entire chat history. This creates a powerful hybrid of Google's intent-based advertising and Meta's interest-based profiling, going beyond simple sponsored links to offer deeply contextual promotions.

An 11-year Meta veteran explains that Facebook's ad value shifted from demographics to interest targeting, and now to a sophisticated AI. Today, the best strategy is often to remove granular targeting and let the system's machine learning find the right audience automatically.