Most marketing agencies think they’ve made the shift. They’ve added “AI-powered” to their website, run a few ChatGPT prompts for client deliverables, and nodded along at the last industry conference when someone said the future is now.
It’s no secret that AI is reshaping marketing agencies, but we wanted to know how.
In our latest survey, we identified that clients aren’t just expecting AI fluency anymore. And agencies that haven’t made the hard structural shift from execution to strategy are losing ground, not gradually, but fast.
To access our marketing agency AI report, we asked you to answer one simple question:
And a lot was revealed.
We didn’t just want theory. So we asked, and here’s what the data revealed.
On the client side: Expectations are moving toward:
This all hinges on the fact that AI can now handle a big part of execution, which is a huge plus for lean internal teams.
On the agency side: The value proposition is moving toward strategy, consulting, and anything AI still struggles with, plus some new capabilities.
The work that retains (and grows) client relationships is moving toward three things:
None of that is surprising. What’s surprising is how few agencies are structurally repositioned to deliver on it.
We didn’t want this to just be insights, so we turned all of this into something usable–an AI marketing agency assessment.
Here’s how it works:
What you get back is a breakdown of:
It takes a few minutes. The output is direct. If you’re curious about where you actually stand, you can take the assessment here.
If your scorecard surfaced real gaps, the next move is structured learning, not more content to read and forget. And CXL’s B2B Marketing and AI and AI Agents for B2B Marketing programs are the perfect place to start.
For live and on-demand AI-focused sessions:
→ Don’t miss out on our 5-day n8n webinar series — ditch manual tasks and lean into automation with leading B2B marketing experts.
Most marketing agencies think they’ve made the shift. They’ve added “AI-powered” to their website, run a few ChatGPT prompts for client deliverables, and nodded along at the last industry conference when someone said the future is now.
It’s no secret that AI is reshaping marketing agencies, but we wanted to know how.
Most agency leaders are asking the wrong questions: “How do we use AI to do our work faster?” and “Do we need fewer content writers?” The question that actually matters—the one that clients are already asking—is simpler and more brutal: “Do we need an agency at all?”
That shift is already happening.
Static data visualization is a silent engagement, productivity, and conversion killer. Marketers have been uploading data to tools like Flourish, Datawrapper, and Tableau for years—then manually formatting, exporting, and embedding the results.
It works, but it’s also slow and what took weeks to create is often lost and forgotten in a four-second scroll.
Google’s AI Overviews don’t just summarize the top result. They cite whoever answers the query best, regardless of whether that page ranks first, fifth, or not at all.
Your brand could be invisible in AI answers while your domain authority sits at 60. That’s the new reality, and most SEO dashboards won’t tell you it’s happening.
Most marketers probably don’t even know if they’re being cited or not. There’s no standard report for this. No toggle in Search Console. No widget in Semrush that shows you, clearly, how often your brand appears in AI-generated answers versus your competitors.
So we built one.
LLM hallucinations are a known issue. But as frustrating as they may be, hallucinated AI citations are just a symptom.
Every time an AI assistant invents a URL to your site—confidently, wrongly—it’s doing so because a real person asked a real question. The model expects your site to have an answer, and when it can’t find one, it fills in the blank.
That’s the gap worth paying attention to.
Google AI Overviews are rapidly becoming the first thing users see for informational queries. That citation layer is increasingly shaping perception before a user even looks at the organic results.
But most teams have no idea whether they’re showing up in these citations or not.
SEO used to reward depth. If your article was an exhaustive piece on a topic that covered every angle and included a few keywords, clicks would usually follow.
Today, search rewards precision over sheer depth.
For the past two years, tracking AI visibility and citations has largely been a black box.
Third-party tools like Semrush and Ahrefs introduced ways to estimate AI visibility by monitoring search results and citations. But until recently, we didn’t have first-party data directly from the search engines themselves confirming when and how often content was used inside AI-generated answers.
That changed a few weeks ago.
The problem with competitor content analysis isn’t that it doesn’t work. It’s that doing it manually at any meaningful scale is unsustainable.
You either do it rarely enough that it’s useless, or you burn your team’s time on a process that collapses under its own weight the moment you try to run it across more than a handful of keywords.
Most educational content shows you the polished end result. The best practices, the final framework, the “what works.”
But what often gets left out are the setbacks, the failed experiments, and the messy process that actually leads to those results.
That’s the gap we’re closing with this new series.