Tools: LinkedIn's AI Post Generator: The Good, The Bad, and The Surprisingly Human

What LinkedIn's AI Actually Does (And Doesn't) ## The Brand Voice Problem Nobody's Talking About ## The Smart Way to Use LinkedIn's AI Generator ## Use It as a Research Assistant, Not a Writer ## Let It Handle the Boring Stuff ## Treat It Like a First Draft from an Intern ## The Authenticity Hack That Actually Works ## What the Algorithm Actually Rewards (Spoiler: It's Not What You Think) ## The Future of AI-Assisted Personal Branding ## Practical Guidelines for AI-Enhanced Authenticity ## The Bottom Line LinkedIn's AI post generator landed with the subtle fanfare of every new AI feature these days—promising to revolutionize your content creation while you sip your morning coffee. Because clearly what LinkedIn needed was more posts that sound exactly the same. But here's the thing: I've been testing it for the past few months, and it's not entirely terrible. The trick is knowing when to use it and when to ignore its suggestions completely. Let's start with reality. LinkedIn's AI post generator analyzes your writing patterns, suggests content based on trending topics in your industry, and can draft posts from simple prompts. It's basically a very sophisticated autocomplete that's read way too many thought leadership posts. The good news? It's surprisingly decent at structure. Give it a prompt like "tips for remote team management" and you'll get a coherent post with bullet points, relevant hashtags, and even some industry-appropriate buzzwords. The not-so-good news? Every other marketing director is getting similar suggestions. The result is a LinkedIn feed that increasingly feels like it was written by the same overly enthusiastic intern. I tested this by giving the same prompt to the AI on five different accounts across various industries. The posts weren't identical, but they shared an unmistakable sameness—the same cadence, similar opening hooks, and that peculiar AI optimism that never quite sounds human. Here's where things get interesting. Your brand voice isn't just what you say—it's how you think. Take Gary Vaynerchuk's LinkedIn presence. Love him or hate him, you know it's him within the first sentence. The AI might capture his energy level, but it misses the specific way he connects wine knowledge to business strategy, or how he references his immigrant parents' work ethic. Or consider someone like Ann Handley from MarketingProfs. Her posts have this conversational intelligence that comes from years of translating complex marketing concepts into accessible language. An AI can mimic the structure, but it can't replicate the specific metaphors she draws from her experience as a journalist. The AI learns patterns, but patterns aren't personality. After three months of experimentation, here's what actually works: I've found the AI most valuable for identifying trending topics in my industry. Instead of letting it write the post, I use its suggestions to understand what conversations are happening, then write my own take. For example, when it suggested a post about "AI in marketing workflows," I didn't use its draft. Instead, I wrote about the specific moment I realized our team was spending more time managing AI tools than actually creating content. That's a story only I could tell. The AI is excellent at generating lists, formatting suggestions, and hashtag research. It's terrible at nuance, personal anecdotes, and contrarian takes. I'll use it to structure a "5 lessons learned" post, but I write the actual lessons myself. It saves time on the framework while preserving the insights that matter. You know that intern who's smart and eager but hasn't quite developed a voice yet? That's LinkedIn's AI. It gives you something to react against. Sometimes I'll generate a post, read it, and think "That's exactly what everyone expects someone in my position to say." Then I write the opposite. Or I find the one line that feels authentic and build around that. Here's something I discovered by accident: the AI is terrible at personal details, but great at professional frameworks. So I started using it backwards. I'll write the personal story or specific example first—the thing that happened in yesterday's client meeting, the mistake I made last quarter, the unexpected insight from a conference conversation. Then I'll ask the AI to help me structure it into a broader lesson. It's like having a writing partner who's really good at organization but terrible at life experience. This approach lets me keep the human elements while benefiting from AI's ability to create clear, scannable content that performs well on LinkedIn's algorithm. LinkedIn's algorithm has gotten more sophisticated about detecting AI-generated content. Not because it's trying to punish AI use, but because engagement patterns reveal authenticity. Posts that generate genuine comments and conversations perform better than posts that collect likes and generic "great insights!" responses. The AI tends to produce content that gets polite engagement—the LinkedIn equivalent of small talk. Authentic posts, even imperfect ones, tend to generate real discussions. People respond to specificity, vulnerability, and genuine expertise in ways they don't respond to optimized content. I've noticed this in my own analytics. My highest-performing posts from the past quarter were the ones where I shared specific failures, unpopular opinions, or behind-the-scenes details from actual projects. The AI-assisted posts performed adequately but rarely sparked meaningful conversations. This isn't going away. If anything, AI writing tools will get better at mimicking individual voices. The question is whether we'll all sound increasingly similar or whether we'll get better at using these tools to amplify our authentic selves. I think the winners will be people who treat AI as a research and organization tool rather than a replacement for their own thinking. The losers will be those who outsource their voice entirely and wake up one day wondering why their content feels generic. The irony is that as AI gets better at producing "good" content, the value of genuinely personal content increases. Being human becomes a competitive advantage. Here's what I've learned works: Always start with your own idea. Use AI to help structure or research, but begin with something only you could say. Edit ruthlessly for voice. AI tends toward corporate speak. Replace "leverage" with "use." Change "optimize" to "improve." Make it sound like you actually talk. Add specific details. Names, numbers, dates, locations. The AI deals in generalities. You deal in specifics. Include your opinions. The AI is diplomatically neutral. You presumably have thoughts about your industry that go beyond "it's important to stay updated." Test the personal story rule. If you could swap out any name and the post would still make sense, it's too generic. Add something that could only come from your experience. LinkedIn's AI post generator is a tool, not a strategy. It's useful for the same reason spell-check is useful—it handles the mechanical stuff so you can focus on the important parts. The important parts are still your ideas, your experiences, and your perspective on your industry. Those can't be automated, and they shouldn't be. Use the AI to save time on formatting and research. Use your brain for everything else. Your audience will notice the difference, even if they can't quite articulate why. Because at the end of the day, people connect with people, not with perfectly optimized content that could have been written by anyone. And in a world where anyone can generate professional-sounding posts, being genuinely yourself becomes the ultimate differentiator. 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