Contrary to popular belief, the rise of AI tools like ChatGPT isn't causing a decline in Google search volume. Instead, users are supplementing their existing search habits with new AI tools, leading to a more fragmented, but not shrinking, research landscape.
Optimizing for AI is not a task for a single team. It requires a holistic, coordinated effort across brand, content, lead gen, and ABM teams to ensure all content is consumable by LLMs in a consistent and desirable way, preventing misinterpretation of the brand's narrative.
Unlike traditional search engines where "evergreen" content can perform well for years, LLMs place a higher value on the freshness of content. To stay relevant in AI-driven search, marketers must consistently update, iterate on, and expand upon their core content pieces.
AI-powered search results create a confusing analytics signal. Marketers may see search impressions increase significantly while simultaneously witnessing a sharp decline in click-through rates and website traffic, as users get answers directly on the search page.
The first step to influencing AI is ensuring your website is technically sound for LLMs to crawl and index. This revives the importance of technical audits, log file analysis, and tools like Screaming Frog to identify and remove barriers preventing AI crawlers from accessing your content.
To shape the narrative presented by AI, valuable content previously hidden behind lead-gen forms (like PDFs and whitepapers) must be made publicly accessible. LLMs cannot consume gated content, so making it public and structuring it for them is crucial for your value propositions to be accurately represented.
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.