There’s a delightful irony in discovering that artificial intelligence has mastered the art of corporate speak before mastering actual human communication. According to a recent study by Originality AI, more than half of LinkedIn’s longer posts are now AI-assisted, which explains why scrolling through LinkedIn feels increasingly like reading a procedurally generated management consultant simulator.
The fascinating aspect isn’t just the prevalence of AI content, but how seamlessly it blended in. Consider this: LinkedIn inadvertently created the perfect petri dish for artificial content. The platform’s notorious “professional language” had already evolved into such a formulaic pattern that it was essentially a compression algorithm for human status signaling. When you think about it, corporate speak is just a finite set of interchangeable modules: “leverage synergies,” “drive innovation,” “thought leadership,” arranged in predictable patterns to signal professional competence.
From a computational perspective, this makes perfect sense. Corporate language isn’t really a natural language - it’s more like a protocol, a formalized set of signals that humans developed to navigate professional hierarchies. And protocols are exactly what machines excel at implementing. The moment ChatGPT appeared, it didn’t need to learn how to think or understand - it just needed to pattern-match its way through the established corporate grammar.
What’s particularly fascinating is the feedback loop this creates. Humans write corporate posts, AI learns from these posts, generates similar content, humans read and internalize this AI-generated content, and then produce more content influenced by it. We’re witnessing the emergence of a new linguistic variant: Corporate Pidgin, a hybrid language optimized for neither human understanding nor machine efficiency, but for perpetuating itself through the LinkedIn ecosystem.
The numbers from the study tell an interesting story. That 189% increase in AI usage from January to February 2023 isn’t just a statistical blip - it’s the moment when the corporate hivemind discovered it could outsource its signaling behavior to machines. And why wouldn’t it? If the goal is to maintain professional presence while saying as little as possible of substance, AI is the perfect tool for the job.
But here’s where it gets really interesting: LinkedIn’s response to this phenomenon reveals a deeper truth about our digital social spaces. When their Head of Feed Relevance says they have “robust defenses” against “low-quality” content, they’re missing the point entirely. The problem isn’t low-quality content - it’s that we’ve created an environment where the distinction between high-quality and low-quality content has become computationally impossible to determine.
Think about it: if a human writes a post full of corporate buzzwords and meaningless platitudes, is it more or less authentic than an AI generating the same content? If an AI writes a thoughtful, well-researched analysis, is it less valuable than a human’s rushed, poorly thought-out post? We’re entering a phase where the traditional markers of content quality are becoming decoupled from their original purpose.
This is where the computational metaphor of corporate communication breaks down in an interesting way. In information theory, a signal becomes less useful as noise increases. But in the LinkedIn ecosystem, the noise IS the signal. The ability to generate and propagate corporate speak, regardless of its information content, has become a form of social capital in itself.
What we’re really observing is the emergence of a new form of artificial life - not the kind that thinks and feels, but the kind that replicates and evolves. Corporate communication patterns are behaving like self-perpetuating memes, using both human and artificial hosts to propagate themselves through the professional network.
The real question isn’t whether AI is generating content on LinkedIn - it’s whether we can still distinguish between authentic professional discourse and the emergent patterns of our own creation. We’ve built a system that optimizes for engagement over authenticity, for pattern-matching over genuine insight, and now we’re surprised that machines have become better at playing this game than we are.
Perhaps the most amusing part is that this might actually be an improvement. If we’re going to have meaningless corporate speak, we might as well have it generated efficiently by machines, freeing up human bandwidth for more meaningful forms of communication. Or maybe this is how it ends - not with artificial general intelligence taking over the world, but with all professional communication gradually dissolving into an incomprehensible soup of AI-generated corporate jargon.
The next time you’re scrolling through LinkedIn and find yourself nodding along to a post about “leveraging dynamic synergies to drive transformative innovation in the digital age,” take a moment to appreciate that you might be participating in one of the largest unintentional experiments in artificial social evolution. We set out to build professional networks, and instead, we might have created the first artificial corporate ecosystem.
And remember, as the old saying goes: if you can’t tell whether a LinkedIn post was written by a human or an AI, does it really matter? The machines have already won - they just had to learn to speak corporate first.