AI in Marketing

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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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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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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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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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.

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AI agents for B2B marketing

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