LLMs frequently cite sources that rank poorly on traditional search engines (page 3 and beyond). They are better at identifying canonically correct and authoritative information, regardless of backlinks or domain authority. This gives high-quality, niche content a better chance to be surfaced than ever before.

Businesses excelling at traditional SEO can still be invisible to AI-powered search engines. AI prioritizes structured data (schema) and directory signals differently than Google's algorithm. A separate strategy for "Answer Engine Optimization" (AEO) is now required.

LLMs can actually benefit sites with deep, authoritative content, even if it's not ranked #1 on Google. AI models prioritize surfacing the best answer, regardless of traditional rank, potentially increasing traffic for subject matter experts.

Unlike traditional SEO, AI-generated answers are personalized based on a user's entire conversation history. Two people can get different results for the same prompt. Therefore, chasing keywords is a flawed strategy. Brands should instead focus on building a deep, structured, authoritative data foundation that the AI can interpret for any context.

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.

Google's AI search panels intercept user queries, causing massive click-through rate drops (up to 89%) for even the highest-ranking organic results. This breaks the long-standing model where top rankings directly translated to traffic and revenue, making traditional SEO metrics obsolete.

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.

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.

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.