The awareness and problem-solving stages of the buyer's journey, which historically relied on website content and search, are being fundamentally altered. Buyers now use AI to get synthesized, "unbiased" information, bypassing vendor websites entirely for their initial research, thus removing key intent signals for marketing teams.

Consumer search behavior is shifting from browsers to AI assistants. E-commerce brands must adapt by treating agents like ChatGPT as new traffic sources. This requires making product data discoverable via APIs to enable seamless research and purchasing directly within conversational AI platforms.

Traditional websites are static information libraries. As users increasingly conduct their research within AI platforms like ChatGPT, the website's role will shift to become an interactive, "agentic seller" designed for fully-researched visitors seeking a final transaction, not initial discovery.

Contrary to the belief that AI assistants replace search, clickstream data reveals a surprising trend: users who start using tools like ChatGPT subsequently perform *more* searches on Google. This is likely due to fact-checking AI responses or researching concepts and products suggested by the AI.

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.

Shopify's Harley Finkelstein argues agentic commerce will make SEO obsolete. Instead of brands gaming search rankings, AI will recommend products based on merit and a user's personal context history. This shift could level the playing field, allowing smaller, high-quality brands to be discovered more easily.

Google's Universal Commerce Protocol allows users to buy products or book demos directly in AI-powered search results. Marketing success is no longer about site clicks, but about influencing decisions and completing transactions within Google’s ecosystem, a fundamental change for all marketers.

Unlike Google, which primarily handles discovery, AI models engage users in a Q&A process that guides them through consideration. This means when a user clicks through from an AI search, they are highly qualified and ready to convert, explaining the significantly higher conversion rates seen from this traffic source.

AI tailors recommendations to individual user history and inferred intent, such as being budget-minded versus quality-focused. This means there is no single, universal ranking; visibility depends on aligning with specific user profiles, not a monolithic algorithm.