Practical Examples of Human+AI Content Workflows + BOFU Content Strategy Survey
How marketers are blending human expertise with AI efficiency to scale quality without losing credibility.
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We’re back for October, breaking down the nebulous idea of Human+AI in marketing and providing four real examples that you can implement for your company.
Cheers,
Nate
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4 Practical Examples of Human+AI Workflows
The best teams aren’t asking, “What can AI do for us?” They’re asking, “Where does human judgment matter most, and how can AI handle the rest?”
I’m certain you’ve seen things about AI assistance, Human+AI, or Human-in-the-Loop at this point. All are ways of explaining that AI is most helpful when it complements the human, who has the expertise, nuance, and context.
But what does that actually look like? Where do you draw the line on responsibilities?
At Ten Speed, we’ve been experimenting with human + AI workflows across every part of our organic growth programs since ChatGPT was released in 2022. Below are four practical examples that show how humans (and our team) and AI can complement each other in real-life scenarios.
Case Studies
Case studies are one of the hardest assets to scale. They require interviews, data validation, approvals, and storytelling finesse. All things that demand a human touch. But AI can dramatically reduce the time it takes to move from interviews and inputs to polished proof by handling summarization, structuring, and first-draft creation.
Human: Extracts customer stories, validates data accuracy, and sets narrative structure for the case study.
AI: Summarizes call transcripts, drafts 1-pagers, and creates pull quotes or comparison tables.
Example: Marketers interview customers and record calls, then add transcripts, approved data points, and other necessary context into a doc/database. AI transcribes interviews, suggests narrative arcs (“problem → proof → payoff”), and drafts alternate versions for PR pitches or LinkedIn carousels. Humans refine and edit to ensure tone and compliance, then handle publishing and promotion.
Result: Faster production of trust assets that feed into both content and PR workflows.
Organic Social & Distribution
Most B2B teams know they should repurpose content, but the reality is that creating dozens of social posts from a single long-form piece can drain capacity fast. AI helps close that gap by atomizing ideas, testing hooks, and giving strategists a starting point for every platform, while humans maintain voice, nuance, and brand consistency.
Human: Defines distribution strategy, creative pillars, and brand voice.
AI: Atomizes long-form pieces into posts, identifies trending hooks, and drafts captions or comment replies.
Example: Marketers identify long-form content (blog posts, webinars, etc.) that would be a good candidate for social content based on knowledge of ICP and could industry/market conditions, and define tone/style guidelines. AI writes first-draft versions for each platform and/or creates draft video clips; the strategist edits, refines tone, determines sequencing, and schedules them based on goals and broader marketing initiatives.
Result: Consistent cross-channel visibility without diluting expertise.
Digital PR & Outreach
Securing coverage and backlinks still depends on relationships, timing, and editorial instinct…all things that require a human touch. However, AI can handle the heavy lifting that enables those moments.
By scanning thousands of journalist profiles, clustering themes, and summarizing coverage, AI gives PR teams better context before they ever send an email.
Human: Builds relationships, sets editorial angles, and personalizes outreach.
AI: Scans media databases, summarizes journalist coverage, and drafts personalized outreach based on patterns.
Example: Marketers use AI to cluster relevant reporters and summarize their latest coverage themes. Humans then tailor personalized story pitches and proof points.
Result: AI accelerates research; human judgment drives placement success.
Thought Leadership & POV Content
Publishing thought leadership consistently is hard, especially when every post needs to sound like an executive and not a template.
An exec publishing AI-generated slop can also have the opposite effect, destroying credibility and authority, so this is definitely a tricky one!
Human: Sets the agenda/questions, interviews the exec, documents personal anecdotes, and adds company and market context.
AI: Suggests counterarguments, transcribes interview recordings, creates post outlines, and title/headline options.
Example: Marketers craft a LinkedIn series concept for the CEO based on recent industry developments. They interview the CEO, then feed the transcripts, company information, tone/style guides, and other necessary context. The AI creates an outline or rough draft, suggests supporting data and structures, and pulls direct wording from transcripts where possible. Marketers refine and edit to ensure nuance and credibility.
Result: Stronger, faster publishing cadence that scales executive visibility.
The Takeaway
These workflows work because they respect the balance between human context and data processing. AI handles the repetitive, data-heavy steps; humans focus on the parts that require interpretation, trust, and taste.
Teams that master this mix don’t just produce more content; they produce content that performs better, builds brand authority faster, and creates measurable impact across every channel.
📚 What the Ten Speed team is reading…
Third-Party Sources Drive 85% of Brand Discovery (AirOps)
Introducing Clearscope 2.0 (Clearscope)
Executive Alignment in the GEO Era (Ten Speed)
Our BrightonSEO 2025 Takeaways (Ten Speed)
Footnotes
A few other things from Ten Speed…
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Spot on. This distinction between human judgement and AI assistance is key to actual progress. Are you finding that marketers are realy embracing this workflow yet?