Effective Answer Engine Optimization (AEO) isn't about traditional keywords. It requires creating hundreds of niche content variations to match conversational queries. Furthermore, it involves a targeted "citation" strategy, focusing on getting mentioned on platforms with direct data licensing deals with specific LLMs (e.g., Reddit for ChatGPT), as these are prioritized sources.

In Generative Engine Optimization (GEO), social media's direct influence on being cited by AI is surprisingly minimal (<1%). AI models prioritize high-authority sources like credible media and directories, forcing a re-evaluation of channel importance for discoverability and challenging a decade of digital marketing orthodoxy.

Earned media is a primary source for generative AI, appearing in over 60% of brand reputation-related responses according to research. This positions PR at the center of the new "Generative Engine Optimization" (GEO) landscape, creating the most significant strategic opportunity for the industry in over a decade.

While competitors focus on subscription models for their AI tools, Google's primary strategy is to leverage its core advertising business. By integrating sponsored results into its AI-powered search summaries, Google is the first to turn on an ad-based revenue model for generative AI at scale, posing a significant threat to subscription-reliant players like OpenAI.

As AI devalues simple clicks, marketing focus must shift to building a strong brand that algorithms recognize as authoritative. High-quality, well-structured owned content (like blogs and reports) becomes more critical for discoverability than traditional performance marketing tactics.

AI models heavily weigh earned media from credible publications when determining brand authority. With 61% of AI brand mentions coming from editorial sources, PR is no longer just a brand-building exercise but a critical technical lever for GEO, directly influencing discoverability.

Unlike traditional SEO where the top link wins, in LLMs, the answer is a summary of many sources. The brand mentioned most frequently across all citations is most likely to be recommended, even if it's not the top-ranked source. This changes the strategy from ranking to saturation.

Unlike Google Search, which drove traffic, AI tools like Perplexity summarize content directly, destroying publisher business models. This forces companies like the New York Times to take a hardline stance and demand direct, substantial licensing fees. Perplexity's actions are thus accelerating the shift to a content licensing model for all AI companies.

Instead of short-term data licensing deals, Perplexity is building a publisher program that shares ad revenue on a query-level basis. This Spotify-inspired model creates a long-term, symbiotic relationship, incentivizing publishers to partner with the AI platform.