Appearing prominently in AI search engine answers is becoming critical for marketers, so posting content on LinkedIn can seem to many like time well-spent.
But a dive into generative AI's authority frameworks — the technical mechanisms and conceptual approaches that large language models (LLMs) use to determine the credibility of information and sources — suggests all that posting effort is more of a placebo for visibility-hungry marketers.
There's considerable evidence — including direct output from ChatGPT itself — that LinkedIn posts don't carry enough authority weight to land a company or an expert in an LLM's answers.
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Growing use of LinkedIn
The continuing steep growth of both users and revenue at LinkedIn provides evidence of business professionals pouring more time and energy into the social media platform. The Microsoft-owned site says that 1.8 million feed updates are viewed every minute on the platform.
That has caused a proliferation of low-cost services and AI-powered tools that will create LinkedIn content on a company's or executive's behalf.
Companies such as Manila-based MicroSourcing, for instance, will outsource LinkedIn posts for you using "dedicated Filipino teams," while other platforms, such as Hootsuite and Grammarly, will give you a free AI-powered tool to generate LinkedIn posts.
But while generating low-cost posts might provide comfort for anxious chief marketing officers, the authority frameworks of generative search engines don't reward or elevate posters based on volume.
These frameworks serve as a kind of information filter, seeking to pull out low-credibility sources and provide a kind of machine-vetting for the answers it provides.
AI models such as OpenAI's ChatGPT series and Google's Gemini evaluate content through five primary lenses:
Source reputation. The digital provenance of an article matters, so the authority attributed to a piece published in The New York Times, recent questions about political bias notwithstanding, will rank very highly, as will pieces published in academic or legal journals.
Most trade news outlets retain a high degree of authority, despite that industry's financial decline.
But LinkedIn, as a platform, sits low in this hierarchy because of its social media structure and high volume of self-promotional and AI-generated material — which authority frameworks, ironically, don't like one bit.
Semantic authority. Search engines assess the tone, precision and evidentiary quality of a piece. They like formal patterns of language that connote authority. LinkedIn posts lean toward conversational, promotional or vernacular language.
Citation networks. Authority frameworks rank content that's frequently cited by other authoritative sources very highly.
Think of Marc Andreessen's Software Eats the World essay, published in The Wall Street Journal in 2011, which has been cited and linked to repeatedly for more than a decade.
LinkedIn posts almost never generate this kind of downstream citation.
Content coherence. Engines evaluate whether the piece hangs together factually and analytically. It looks for focus and depth. Shallow or contradictory posts score poorly. Most LinkedIn posts aren't developed with that level of care, focus or thoroughness.
5. Temporal relevance. Timeliness matters, but only alongside the other factors. LinkedIn can deliver timely commentary, but it's not enough to offset the other weaknesses.
Even though some pre-2023 LinkedIn data was used by OpenAI to train ChatGPT, standard LinkedIn posts don't register highly enough on those five AI authority angles to move the visibility needle.
AI-generated posts unlikely to show up in AI search
If a LinkedIn post is AI-generated, as more than half of longer-form posts on the platform were shown to be in a recent study, the chances of it helping a firm show up in AI results are negligible.
This is why an aggressive stream of LinkedIn posts, however well-meaning, rarely improves individual or company visibility where it really matters: Inside the AI engines that are increasingly shaping commercial discovery.
It's a vexing problem, given that traditional search results differ so dramatically from the answers that AI presents.
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A quick search for any specific business-related term can quickly illustrate just how big the problem is.
For example, a standard Google search for "best non-Big Four accounting firm for quality of earnings work" returned about 300 results spread across 20 pages. That includes accounting firm websites, sponsored ads splashed across every results page and numerous "guide to best accounting firms" articles.
The same prompt given to ChatGPT returned the names of five firms, with a detailed description of why each made that shortlist. The five that did had a digital authority trail.
The 85,000 accounting firms that didn't make ChatGPT's list? They're invisible to the person making the inquiry.
What does this mean for experts?
A new kind of "publish or vanish" dynamic has arrived, paralleling the old "publish or perish" maxim in academia.
The best advice is to pour more focus and effort into work that can actually earn an authoritative, high-provenance publication rather than effecting a "spray and pray" strategy on LinkedIn.
LinkedIn has important uses as a business directory and a tool for recruiting and networking.
But expecting it to be the engine of an AI visibility strategy is like training for the Olympics by walking around the block: It isn't harmful, but it isn't getting you any closer to gold either.
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