Ben Thompson argues AI apps should adopt a Meta-style advertising model based on deep user understanding, rather than Google-style contextual ads tied to prompts. This avoids conflicts of interest and surfaces products users didn't know they needed, creating more value for both users and advertisers.

Traditional SEO often involves technical debates (e.g., subdomains vs. folders) and link building. In contrast, optimizing for AI search (AIO) is about teaching the LLM about your product's value, features, and benefits, much like training a salesperson. It requires strong product marketing skills over technical SEO expertise.

AI conversations capture high-intent moments, allowing ads to target active decision-making rather than passive attention-grabbing like social media. This fundamental difference could lead to significantly higher average revenue per user (ARPU), making social media's ad performance a floor, not a ceiling for AI platforms.

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.

Instead of traditional cost-per-click models, ChatGPT could pioneer a "verified outcome" system where advertisers pay only upon a completed transaction and user satisfaction. This would inherently favor advertisers with superior products that lead to actual conversions, improving ad quality and relevance for all users.

In AI-driven commerce, brands win by being selected by an agent, not by ranking on a search page. This shift favors brands with trustworthy, structured, and verifiable data over those with the largest advertising budgets, leveling the playing field for smaller, agile companies.

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.

Unlike older search algorithms gamed by keywords, AI has the potential to identify and surface genuinely useful and trustworthy content. This shift could benefit expert-driven media and creators by rewarding depth and authority over optimization hacks, leading to a 'return to trust.'