Authenticity vs. Algorithm in the Age of AI
Letâs not sugarcoat it; the way content gets seen online is changing fast, and not always in ways that make sense. If youâve been clinging to keyword density or backlink volume like theyâre still the holy grail, this weekâs news might feel like a cold splash of reality. Because the question is no longer just how your content performs, itâs whether it even counts as a signal anymore.
LinkedIn: A Case Study in Human-Led Growth
Take LinkedIn, for example. HubSpot just published a breakdown of how one CEO pulled in 3 million impressions in four months. No ad spend, no automation, no âyou wonât believe what happened nextâ clickbait. Just five things: a strong point of view, clear content pillars, earned credibility (think podcasts or panels), a consistent three-posts-a-week rhythm, and constant tweaking based on what actually worked. Thatâs it. No gimmicks, no growth hacks. Just a human being talking to other humans, regularly and with purpose.
And hereâs the kicker; it didnât just generate likes. It brought in demo requests, sales calls, real pipeline. The takeaway? Executive presence, when done right, isnât a vanity metric. Itâs a growth lever.
Google’s AI Overviews: A Feedback Loop of Sameness
Now, contrast that with whatâs happening over on Google.
Ahrefs ran the numbers on Googleâs new AI Overviews and found that nearly 88% of the sources cited were AI-generated. Not AI-assisted; fully AI-written. Only 8.6% came from purely human-written content. To be fair, this isnât necessarily Google playing favorites. Itâs more like a mirror held up to the current state of the web, where three-quarters of new content has some AI in its DNA.
But hereâs where it gets messy. When AI starts citing other AI, you get a kind of feedback loop, a closed circuit of recycled phrasing and secondhand ideas, all dressed up as authority. And for marketers whoâve spent years playing the SEO gameâoptimize, rank, get citedâitâs a gut punch. Because what good is a citation if itâs buried in a sea of synthetic sameness?
Two Signal Models: Human vs. Machine
So now weâve got two very different models of signal.
One is human-led: deliberate, consistent, rooted in credibility and craft. The other is machine-fed: fast, derivative, and increasingly self-referential. And while both might technically âwork,â only one builds trust. Only one leads to actual business outcomes.
The Hard Choices Ahead
Which brings us to the hard part. If youâre leading a marketing team right now, youâre not just competing for attention; youâre competing for meaning. And that means making choices about how you show up. Do you chase the algorithm, or do you build something people actually want to read? Do you publish more, or publish better?
You know what? Itâs not even about volume anymore. Itâs about voice. And voice canât be faked. Not for long, anyway.
Resources Worth Your Time
So whatâs worth your time this week? A few extras, if youâve got the tabs to spare:
- If youâre stuck on messaging, HubSpotâs roundup of 27 Copywriting Examples That Actually Convert is surprisingly solid. Not all of them are genius, but the ones that are? Worth stealing.
- For anyone in the legal spaceâor selling into itâthe Best CRMs for Legal Businesses in 2025 guide is refreshingly practical. No fluff, just tools that actually fit the way lawyers work.
- And if youâre planning next yearâs budget, the Top Marketing Conferences to Attend in 2025 list from Ahrefs is a decent starting point. A few usual suspects, a few curveballs.
The Bottom Line
The platforms are shifting. The signals are mutating. But people still want to hear from people. And thatâs something no algorithm can replicate. Not yet, anyway.
That’s it for today, folks.
Catch you in the next post.
Until then, keep building.
â Perfect Sites Blog