AI in Marketing Archives -

The AI maturity benchmark report: where marketers stand in 2026

Most marketers will tell you they use AI every day. What the data shows is a different story.

A few weeks ago, we launched an AI skills assessment to help marketers identify where they actually stand, whether they’re AI-assisted, AI-integrated, or truly AI-native. The assessment was built to measure real competency across five areas: workflow, production, research, analytics, and AI operations.

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The 5 skills modern marketers need to become AI-native

AI-assisted marketers are becoming more replaceable. Marketers who build AI systems around their work are becoming more valuable, more in demand, and harder to compete with.

That’s not speculation. Over the past few months at CXL, we surveyed hundreds of B2B marketers and analyzed how AI is reshaping marketing roles, workflows, and organizational expectations.

The clearest signal from our research: becoming an AI-native marketer is where the industry is heading, and increasingly what companies are hiring for.

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AI in marketing job descriptions: What 1,750 job posts reveal

The change in skills requirements for AI in marketing jobs has gotten very specific very fast.

We scraped around 1,750 marketing job descriptions across two periods: roughly 1,000 from January 2026 and 750 from May 2026. Four months of job description data doesn’t sound like much. But when mentions of “AI tools” in marketing job descriptions triple, and specific tools like Claude quadruple, four months is significant enough.

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Google’s AI search optimization guide is right about the basics

Last week, Google published its first official guide on generative AI optimization, and it’s the reset a lot of marketing teams needed.

Every week brings a new batch of AI-search optimization “hacks,” like llms.txt files, content “chunking”, AI-specific schema, or inauthentic brand “mentions”, and most of them aren’t worth the time. Google’s guide cuts through it.

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How teams use AI in B2B marketing in 2026

AI adoption in B2B marketing is accelerating. Effective AI adoption, however, is not.

Our research suggests most marketers are still applying AI tactically rather than systematically, focusing on tools instead of building scalable operating systems.

To understand what’s really happening beneath the hype, we combined behavioral and survey data.

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AI Overwhelm: Why marketers are burning out trying to learn AI

When it comes to AI adoption, the dominant narrative amongst marketers is that they’re falling behind. That every new tool, every new model, every new AI marketing workflow announced on LinkedIn is a gap you need to close—now. And the more you scroll, the more that feeling compounds.

The anxiety isn’t irrational, but the response to it usually is.

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GitHub for marketing: Build AI systems that actually scale

More than 150 million people use GitHub. Developers created more than 230 new repositories every minute last year, and there are 4.3 million AI projects on the platform.

Most of those users are still developers. But the profile is shifting.

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Why your pages aren’t surfacing in ChatGPT citations (And how to fix it)

ChatGPT skips web search entirely on roughly 65% of queries. This means (optimized or not, indexed or not), if the model already has the answer, the content you published last Tuesday never had a shot.

The AI search optimization industry has built an entire content category around a behavior that not only happens a third of the time, but is actively declining.

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How to build a competitor ad intelligence tool (and catch who’s bidding on your brand)

You already know competitors are targeting category keywords—it’s baseline and relatively easy to monitor. What most paid search teams don’t have visibility into is who’s bidding on their brand terms.

Not their category but their name, and it happens more than you’d expect.

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A simple framework for teaching LLMs your tone and style

For the past two years, the dominant advice in B2B content marketing has been some version of: be careful with AI. Don’t let it water down your brand. Keep a strong human in the loop. Avoid the slop.

That advice made sense when it was speculative. It makes less sense now that we have data.

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AI in Marketing

The AI maturity benchmark report: where marketers stand in 2026

The 5 skills modern marketers need to become AI-native

AI in marketing job descriptions: What 1,750 job posts reveal

Google’s AI search optimization guide is right about the basics

How teams use AI in B2B marketing in 2026

AI Overwhelm: Why marketers are burning out trying to learn AI

GitHub for marketing: Build AI systems that actually scale

Why your pages aren’t surfacing in ChatGPT citations (And how to fix it)

How to build a competitor ad intelligence tool (and catch who’s bidding on your brand)

A simple framework for teaching LLMs your tone and style

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