A ghostwriter is generating 20 times the LinkedIn reach of creators at his own account size without relying on AI tools, according to Inc.com. The story suggests that human-written, personalized content—rather than AI-generated material or platform hacks—drives disproportionate engagement on LinkedIn. This counters the prevailing assumption in creator circles that scale requires outsourcing to automation.
What this means for LinkedIn practitioners
The findings challenge a core belief that’s been spreading through LinkedIn strategy circles: that volume and speed trump everything else. If a ghostwriter can outperform his peer group by a factor of 20 without AI, it means the platform still rewards something that algorithms haven’t commodified yet—probably authenticity, specificity, or genuine expertise that comes through in the writing itself.
For people building personal brands on LinkedIn, this is permission to slow down. You don’t need to post daily, use AI to generate ten variations of the same thought, or jump to the latest prompt-engineering technique. The outperformance suggests the real edge lies in knowing your audience well enough to write for them specifically, rather than writing for the algorithm or a generic “professional.”
This also matters for hired ghostwriters and content agencies who work with executives and founders on LinkedIn. If human-written, tailored work genuinely performs better, the economics flip: you can charge premium rates for real writing rather than competing on the basis of how many pieces you can churn out per week. The race to the bottom on ghostwriting rates suddenly looks like the wrong strategy.
The implication for your own LinkedIn strategy is direct: if you’re creating content yourself or paying someone to create it for you, the ROI probably lives in depth, specificity, and point of view—not frequency or format optimization.
Our take
We’re skeptical this is as clean a story as the headline suggests. A ghostwriter’s performance doesn’t automatically prove that AI is worse; it might prove that he’s better at his job than most creators are at theirs. Selection bias runs deep here. The people getting 20 times less reach might be using AI badly, posting inconsistently, writing about nothing, or simply lack the writer’s instinct for what resonates.
That said, the broader insight is sound: LinkedIn still rewards signal over noise. The platform’s algorithm hasn’t fully rotted into the TikTok-ification that afflicts some social networks. A well-reasoned post from someone with real expertise still outperforms a mass-produced AI summary regurgitating the same three ideas. The ghostwriter’s refusal to use AI is almost certainly less important than his refusal to be mediocre.
The real caution is this: AI isn’t inherently bad on LinkedIn, but it is inherently commodifying. If everyone uses the same tools with the same prompts, the output converges toward beige. The ghostwriter’s advantage might not be that he’s human; it might be that he’s the only one in his category who still thinks. That’s a skill, not a platform feature.
We’d also note that this story lands in a moment when AI evangelists are in full missionary mode, claiming there’s no point in writing anything by hand anymore. Counterexamples are useful for balance. But let’s not swing the other way and declare AI a red herring. The question isn’t AI versus no AI. It’s whether you have something worth saying and whether you’re saying it clearly to the right people. The ghostwriter apparently does both. Most creators don’t.
What to watch
Watch whether LinkedIn’s algorithm begins to detect and downrank AI-generated or templated content. If the platform starts penalizing synthetic writing at scale, the ghostwriter’s advantage becomes a defensible moat, and rates for human-written content climb. Conversely, if reach stays flat regardless of AI use, this story was probably just about one person being unusually good at his craft.
Also monitor how creators respond: will this push them toward hiring better ghostwriters, or will they dig deeper into AI tooling, convinced there’s some prompt formula they haven’t found yet? The gap between signal and noise usually widens before it narrows.
