The practice of planning, producing, and distributing marketing content so a brand earns visibility across both traditional search engines and AI-assisted discovery channels, while also using AI tools to do that work faster.
Definition of “AI Search Marketing”
AI search marketing has two layers that often get talked about as one term.
The first is using AI tools for research, drafting, personalization, and analysis inside an existing marketing process.
The second, more strategic layer, is marketing toward an audience that increasingly discovers brands through AI assistants and chat interfaces rather than typing a query into a search box and scanning a list of links.
Generative engine optimization is the technical and structural foundation: the schema, entity clarity, and page architecture that make a site legible to AI systems.
AI search marketing is the layer above it, deciding what to publish, how to position it, which queries and prompts to target, and how to measure success when visibility no longer means a click.
“AI Search Marketing” In Practice
A growing share of research now starts with a conversational prompt, such as 'what's the best CRM for a 5-person agency' or 'find me a healthcare marketing partner that understands compliance.'
The assistant doesn't return a list of links to evaluate, it returns a short, synthesized recommendation, sometimes naming two or three brands.
AI search marketing means making sure a brand, its offers, and its proof points are part of what these systems can find and confidently summarize when that prompt gets typed.
Worth Knowing
Click-based metrics undercount AI search marketing performance, since many AI answers satisfy the user without a visit.
Useful signals instead include branded search volume over time, direct and referral traffic from AI assistant domains, and mentions of the brand inside AI-generated answers.