The traditional goal of winning hearts and minds is now a two-step process. Marketers must first win over the "machines"—search algorithms and LLMs—that control 85% of content discovery, treating them as an influential, gatekeeping audience.

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The audience for marketing content is expanding to include AI agents. Websites, for example, will need to be optimized not just for human users but also for AI crawlers that surface information in answer engines. This requires a fundamental shift in how marketers think about content structure and metadata.

In an AI-driven world, optimizing for website traffic is a losing game. A better long-term strategy is to create high-value content (podcasts, videos, newsletters) across various platforms. This approach helps people directly and simultaneously feeds the large language models that are increasingly becoming information gatekeepers.

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.

Users now ask AI models highly specific, long-form questions, not short search terms. HubSpot's CEO advises creating more detailed content with better citations and case studies to provide authoritative answers for these complex queries and remain visible.

With 80-90% of AI-powered searches resulting in no clicks, traditional SEO is dying. The new key metric is "share of voice"—how often your brand is cited in AI-generated answers. This requires a fundamental strategy shift to Answer Engine Optimization (AEO), focusing on becoming an authoritative source for LLMs rather than just driving website traffic.

The rise of AI agents means website traffic will increasingly be non-human. B2B marketers must rethink their playbooks to optimize for how AI models interpret and surface their content, a practice emerging as "AI Engine Optimization" (AEO), as agents become the primary researchers.

Marketers must evolve from SEO to GEO, optimizing content for how brands appear in LLM results. This requires a new content strategy that treats the LLM as a distinct persona or channel, creating content specifically for it to crawl and ensuring accurate brand representation.

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.

Brands will need a bifurcated approach for marketing. One strategy will focus on creating authentic content for human connection, while a separate, distinct strategy must structure information to be effectively parsed and prioritized by the AI agents that increasingly intermediate the customer journey.

As users increasingly get answers from AI assistants, marketing strategy must evolve from Search Engine Optimization (SEO) to Generative Engine Optimization (GEO). This means creating diverse, authoritative content across multiple platforms (podcasts, PR, articles) with the goal of being cited as a trusted source by AI models themselves.