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2 hours ago
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Every company now uses AI to write their emails, generate their ads, and automate their outreach. The content is polished, optimized, and completely forgettable. Authenticity is about to become the only competitive advantage that matters.
Here’s the problem: everyone thinks they understand what that means.
They don’t.
What Happens When Everything is AI-Generated
We’re heading toward a world where:
Every email you receive was written by AI. Every social post was optimized by AI. Every ad was designed by AI. Every customer service interaction was handled by AI. Every sales pitch was personalized by AI.
The content will be perfect. Professionally formatted. Grammatically flawless. Completely optimized.
And nobody will trust any of it.
Here’s why: AI averages everything.
It’s trained on millions of examples, so it writes at the mean of all that data. Professional but generic. Polished but forgettable. Technically correct but soulless.
When one company uses AI, they get an advantage—faster content, lower costs, better optimization.
When everyone uses AI, everything sounds the same.
The Problem Nobody Talks About
In 12-18 months, you won’t be able to tell what’s real anymore.
Is that email from a person who actually cares about your problem? Or is it ChatGPT’s 10,000th variation on “I noticed your company…”?
Is that founder sharing their real insights? Or did they feed their last 50 podcast transcripts into Claude and ask for a “thoughtful LinkedIn post”?
Is that consultant actually thinking about your specific situation? Or are they using AI to generate a proposal from a template?
You can’t tell. Detection tools are useless—37% false positive rates, meaning they flag human writing as AI more than a third of the time.
More telling: in blind tests, people rated AI-generated content as “more trustworthy” than human writing 63% of the time.
Why? Because it’s polished. Professional. Says all the right things in all the right ways.
Until everyone is polished and professional. Then trust goes to zero.
Why “Be More Authentic” Misses the Point
The standard advice: “Just be more human! Show your personality! Share your flaws!”
Cool. Now you’re competing against infinite AI-generated “authentic” content.
AI can write in a casual tone. It can add personality. It can mimic vulnerability. Feed it enough examples of “authentic” content and it learns the pattern.
The Instagram influencer sharing “real talk” about burnout? Could be AI. The founder posting about their failures? Could be AI. The consultant sharing hard-won insights? Could be AI.
“Authenticity” becomes a style. A tone. A pattern AI can replicate.
That’s not the moat people think it is.
What Actually Matters
Here’s the uncomfortable truth: people don’t buy from “authentic” humans anymore than they buy from AI.
They buy from people who understand their specific problem and can solve it.
The consultant who’s read your actual situation and has relevant experience. The salesperson who understands your industry’s constraints. The expert who’s dealt with your exact failure mode before.
That’s not “authenticity.” That’s specificity.
And specificity is hard to fake—human or AI.
The Two Futures
Future 1: Everyone uses generic AI
Every company uses ChatGPT to write emails, generate content, automate responses.
Everything sounds the same. Trust collapses. Buyers retreat to referrals and known relationships.
The people who already have networks win. Everyone else fights for scraps.
Future 2: Smart people use AI trained on themselves
They capture their specific expertise, judgment, and voice. They train AI to represent THEM specifically—not generic best practices, but their actual approach.
When a prospect talks to their AI, they’re accessing that person’s specific knowledge.
Not a script. Not a template. Not averaged internet wisdom.
Real expertise, scaled.
What This Actually Looks Like
Sarah runs a management consulting practice. She used to spend 20 hours weekly on initial client calls—same questions, same discovery process, same frameworks she’s explained 500 times.
Her Digital Self now handles those conversations. Same frameworks. Same diagnostic questions. Same insights about where companies typically fail.
But when something gets complex—when it requires judgment about a specific edge case or a novel situation—the Digital Self says: “This is outside my training. Let me connect you with Sarah directly.”
Client qualification time: 3 weeks → 2 days.
Qualified leads per month: 8 → 23.
Sarah’s time spent on generic discovery: 20 hours → 3 hours.
Not because it’s “authentic.” Because it delivers HER specific expertise at scale.
The prospects who talk to her Digital Self get the same diagnostic approach she’d give them personally. The weird questions she asks. The frameworks she’s developed over 15 years. The specific pattern recognition that makes her valuable.
When they get on a call with her, they’re not starting from zero. They’re starting from “Sarah’s AI already understood my situation deeply—now I need her judgment on the complex parts.”
Why This is Different From Generic AI
Generic AI (ChatGPT, Claude, etc.): Trained on everything. Writes at the average. Safe, polished, forgettable.
AI trained on YOU: Trained on your specific conversations, decisions, and expertise. Sounds like you. Thinks like you. Represents YOU.
The first can be replicated by anyone. The second is your competitive moat.
The Specificity Test
Here’s how you know if what you’re putting out there—human or AI—actually represents you:
Could any of your competitors have said the same thing?
If yes, it’s generic. Doesn’t matter who wrote it.
If no—if it reflects your specific experience, judgment, or perspective—then it’s valuable.
And if it’s valuable, you should scale it.
What People Will Actually Buy
In an AI world, here’s what creates trust:
Not “I wrote this myself” (you can’t prove that anymore).
Not “I’m being authentic” (AI can fake that).
What works:
Specific knowledge of YOUR situation. Not generic advice. Not universal best practices. Your exact problem, understood deeply.
Judgment about edge cases. The weird scenarios AI doesn’t know how to handle. The “this is outside my training, let me get you to a human” moments.
Track record with your problem. Real examples. Specific outcomes. “I helped 12 companies in your exact situation, here’s what worked.”
That’s the moat. Not authenticity. Specificity.
The Paradox of Scale
You can’t personally respond to 200 inquiries per week. You can’t take every discovery call. You can’t be everywhere.
But you also can’t outsource to generic AI and expect people to trust you.
The answer: Train AI on your specific expertise. Scale what makes you valuable. Keep your time for the complex judgment calls.
People will buy from you because your AI demonstrates your specific knowledge. Because it asks the same diagnostic questions you would. Because it recognizes patterns you’ve learned to recognize.
And when they finally talk to you, they’re already convinced you understand their problem. They just need your judgment on the hard parts.
In an AI world, people buy from people. But not because of "authenticity." Because of specific expertise, demonstrated at scale through AI trained on YOU.
The companies winning 18 months from now won’t be the ones avoiding AI or the ones using generic AI.
They’ll be the ones who captured their expertise and trained AI to represent it.
Build your Digital Self. Scale what makes you valuable. Keep your time for the work only you can do.
