Key takeaways
- 73% of B2B buyers now use AI tools to research vendors and partners before a first call.
- AI engines answer by citing sources with consistent, credible authority, not whoever paid the most.
- If you publish little, you are invisible in the exact place the buying decision now starts.
- A podcast, regular content, and a newsletter give AI a body of work to cite you from.
- The fix is consistency, not virality. The name that shows up most becomes the answer.
A buyer with a problem used to start with a search box and a list of blue links. Today a growing share of them start with a question typed into ChatGPT, Perplexity, or Google's AI answers. They ask who the best provider is, who the go-to expert is, and what the smart take on their problem looks like. The AI answers in a sentence or two, names a few people, and the shortlist is formed before you ever knew the buyer existed.
This is the quiet rewiring of how reputation works. For years, being good and being referable was enough. Now there is a machine between you and the buyer, and that machine has already decided who to mention. The question for every expert, founder, and recruiter is simple. When the AI gets asked about your category, does your name come up?
Why the research moved to AI in the first place
Buyers did not wake up one day and decide to trust a chatbot. They moved because the old way was exhausting. The average B2B buying journey is mostly complete before a buyer ever talks to a vendor. By some estimates, 61% of the decision is made through independent research. People do not want a sales call. They want an answer.
AI gives them that answer faster than ten open tabs ever could. It reads the room, summarizes the options, and hands back a short list with reasons. For the buyer, it is a shortcut. For you, it is a new gatekeeper, and the rules of that gate are worth understanding.
When the AI gets asked about your category, your name is either in the answer or it is not. There is no second page.
How AI engines decide who to name
AI answers are built from patterns in published material. When you ask an engine who the go-to expert in a field is, it is not consulting a directory. It is drawing on the people who appear again and again, across sources, talking with clarity about that exact topic. Three signals do most of the work.
Consistency. One article does not make you the answer. A steady body of work on a focused topic does. The engine is pattern matching, and patterns need repetition.
Specificity. Generalists are hard to cite. The expert who owns a clear, narrow position is easy to surface because the engine can map them cleanly to the question.
Corroboration. A name that shows up in a podcast, in articles, and quoted elsewhere reads as credible. Several sources pointing the same way is exactly the signal these engines reward.
Notice what is missing from that list. Nobody buys their way into the answer. You earn it by being the person the material keeps pointing to.
What this means if you are barely publishing
If your output today is a thin profile and the occasional post, the AI has almost nothing to work with. It cannot cite a body of work that does not exist. So it names someone else, and that someone else gets the consideration, the call, and the close. You are not losing because you are worse. You are losing because you are invisible in the place the decision now happens.
This is the trap for the most capable people in any field. The work is excellent and the visibility is near zero, so the market, and now the machine, defaults to whoever is easiest to find.
How to become the answer
The path is not complicated, but it does demand consistency most people cannot sustain alone. You need a focused topic, a steady stream of substantive material, and enough corroboration across formats that the engines treat you as a reference point. Three assets cover it.
A podcast gives you a recorded, searchable point of view and a roster of credible guests who reinforce your standing. Regular content keeps your take in front of buyers and in front of the crawlers that feed the models. A newsletter builds an owned audience and a high-trust signal that you publish consistently. Together, they give an AI engine a clear, repeated, well-corroborated picture of who you are and what you own.
This is the entire idea behind the Marquee System. One recorded hour a month becomes a month of presence across all three. You bring the expertise. The output that makes you citable gets built for you.
Become the name the answer points to.
We build the podcast, the content, and the newsletter that make you the expert buyers and AI search surface first. Done for you.
Apply to work with the studioFrequently asked questions
What is generative engine optimization?
It is the practice of becoming a source that AI answer engines cite. Where traditional SEO targets ranking on a results page, this targets being named inside the AI answer itself. The mechanics reward consistent, specific, well-corroborated expertise rather than keyword tricks.
Do I need to pay to appear in AI answers?
No. AI engines build answers from published material and the patterns within it, not from ad spend. You earn a citation by being the person the credible sources keep pointing to, which is a function of consistent publishing on a focused topic.
How long does it take to start showing up?
It is a compounding effect, not an overnight one. As your body of work grows and gets reinforced across a podcast, articles, and a newsletter, the odds of being surfaced rise. Most of the value comes from sustaining the output long enough for the pattern to form.
Can a small firm compete with bigger names here?
Yes, and often more easily than in paid channels. Specificity beats size. A focused expert who owns a narrow topic is easier for an engine to cite than a large generalist brand, because the match to the question is cleaner.