60% of Google searches now end without clicking on any content.
That figure forms a key argument from Gabriel Dillon, Go-to-Market Lead for Personalization in Content: when AI makes content almost free to produce, volume ceases to be a strategy. The only content that counts is content that is responsible for reporting on business results, created for a specific person, and measured with real data.
In an SEJ webinar with Solution Chief Content Strategist John Graham, Dillon went over why AI-assisted copy is pulling in regular checkouts, the four questions he asks of all sales copy before it’s sent, and personal branding that works without overwhelming your stack.
The session also covered when a human is part of an AI-assisted workflow, and how testing and personalization fit into an accountability loop for content performance.
Watch the full webinar if you want.
Why Your AI Content Feels Like Everyone Else’s
Your AI writing assistant acts as the last yes man, and your guesses feed the loop. That’s Dillon’s explanation for why each AI-assisted copy of the product converges on the same output.
“Our bias as we write content using robots ends up eating into the content we produce,” he said. “We end up in this cycle of creating content that we think is good but doesn’t do what we think it does.”
The back copy confirms what you already believed or mirrored every competitor’s blog on tools training data. Both results fail the student.
Dillon’s counterweight is taste, and he pushed definition beyond cliche: intuition and emotion, and taking the risk of making a claim no AI tool can volunteer, based on what you really know about your market.
A session is a map of where one steps in an AI-assisted workflow, between AI as a research layer and context and the copy being sent.
How Is Content Management Accountable For Business Results?
Dillon runs the same four questions on every piece of B2B marketing copy before it’s sent.
The first is whether the copy is producing the results you expect. The other three include who the content belongs to, how you identify those people, and how understanding is measured.
“If we don’t have data that proves our content is good, then we can’t think about how to measure it or make it work better,” he said.
Testing and personalization are two halves of the same coin in this model. How these two come together into a system, rather than a series of individual tests, is where the recording goes deep.
Full flow diagrams that draw the accountability loop and test dimensions beyond variation A versus variation B.
Action item: before posting the next batch of AI content, run it against Dillon’s four accountability questions.
What Do-It-Yourself Signs Work Without Bulking Up Your Stack?
Signs your stack is already stacked. Dillon’s diagnosis of why B2B personalization has been under-delivered for years: teams tackle ambitious initiatives, then flounder.
He lays out three categories of signals, starting with the simplest: new visitors versus returning visitors. The first visitor and the repeat visitor have a different purpose, and giving them the same copy of the hero ruins the difference.
The second and third steps are using signals to generate your ad campaigns and loyalty program today. Dillon called the current administration one of them “such a missed opportunity”; recorded words to be used and where each one pays.
The web demo shows how these different emotions are created and delivered within the content. Watch it on demand.
Is Google Punishing AI Content? That’s Zero-Click Shift
Finding the wrong problem to solve, Dillon argued: whether Google can identify AI content is more important than clicks.
Contentful’s customers are already reporting organic traffic crashes as AI snippets drive clicks.
Active feedback is a competitive AI feedback layer. GEO and AEO determine whether the AI summary at the top of the results page shows your product at all.
His conclusion cut to the humans-vs-robots debate: one type of content that generates AI summaries and on-page conversions simultaneously. All you need is that content, and the Content tool you just posted, in the session.
Recording includes a way to deal with GEO and AEO without splitting your content strategy in two.
Q&A: The Most Helpful Questions from the Webinar
Q: After Google’s spam review, does Google remove AI-written content?
Expect AI content identification to continue to get harder; Dillon called it “Google is not going to win.” His direction shifts the focus away from avoiding discovery altogether, to a different place where he argues against news as zero-click search grows. He explains where he will redirect that effort in the program.
Gabriel answered. Get the full context; watch on demand, now.
Q: What do you think critically about inherent biases in AI content?
Bias comes in two places. He injects it with awareness and context, which produces “the desired effect, but perhaps not the most effective effect.” It also resides in the training data itself. Dillon’s reduction begins before you produce anything; he goes through the sequence of his full answer.
Gabriel answered. Get the full context; watch on demand, now.
Q: What do you do when leadership wants AI content in bulk without understanding quality control?
Hold leadership accountable for the performance they expect. “Show them with data that you can create better content that drives the business results you want by creating fewer but better pieces of content.” Dillon also conceded one point in the volume argument, and that consensus fixes the way he makes the case.
Gabriel answered. Get the full context; watch on demand, now.
Q: Do SEO service pages need a unique voice, or can AI write them?
Dillon separates voice from performance. “I don’t think service pages or pricing pages need to be multi-character to be effective.” But even rote pages serve visitors with different goals, and his full answer draws the line at which pages warrant more than AI input.
Gabriel answered. Get the full context; watch on demand, now.
Watch the Full Webinar
The on-demand recording includes a full walkthrough of the accountability, a live demo of building different experiences in Content, John Graham’s field perspective from teams working on this workflow, and session handouts.
Register once to watch on demand.
