Why our human hardwiring still matters — and why AI makes it matter more
Founder & President, JTS Marketing
There’s a version of B2B marketing that works fine. Technically. The product gets described. The features get listed. The LLM produces snappy copy. The campaigns go out. Things move.
For a while.
It’s a bit like filling up a Ferrari with cheap gas. The car will run. You won’t notice the difference on the first few drives. But you’re slowly degrading the GTM/RevOps engine you paid a fortune for — and the performance gap compounds quietly.
The cheap gas, in this case, is the willingness to skip past real human insight and appreciation of how we actually process information, make decisions, and choose to trust — in favor of something faster, cheaper, and more easily generated.
Anyone who has worked in marketing long enough has seen it: the look on the face of an engineering or finance-led founder when you try to talk about brand, narrative, or positioning. Nothing is said. Nothing needs to be. The expression says it all — do I really have to care about this? This all seems so frivolous.
It’s an understandable reflex. People who build deterministic systems — who live in the world of inputs, outputs, and measurable causality — commonly struggle with the invisible systems that make up human behavior and their more probabilistic and emotional nature.
And yet it’s those very invisible, human/social systems that govern whether your product gets remembered, whether your message connects, whether a buyer extends you the benefit of the doubt or puts you on a shortlist.
That’s not soft skills. That’s the game.
B2B tech buyers are not possessed of perfect information and objective reasoning. Research in behavioral economics and decision science has made this definitively clear: they are emotional, status-conscious, and heavily influenced by the opinions of peers — and some well-documented evolutionary hardwiring.
Increasingly, they are called to make decisions as buyer groups, which means individual conviction is rarely enough, making the storytelling far more challenging for junior staff and LLMs to produce. Individuals default to cognitive shortcuts — mental availability, familiarity, category cues — especially under time pressure. And, they are exquisitely sensitive to signals of effort, quality, and care, often in ways they can’t articulate.
This last point matters more than most leaders and marketers acknowledge. Costly signaling theory — the principle that observable signals of effort, skill, and creativity reveal something genuine about the sender — helps explain why a well-crafted piece of writing, an unmistakable visual identity, or a carefully considered point of view still cuts through in a world drowning in copycat, LLM-generated content.
We seem to be wired to recognize quality, even when we can’t define it.
It was (ironically) refreshing to read this week about young AI start-ups investing tens of thousands in human-made videos rather than using LLMs because, they said, “People would know” and “It would just feel very cheap.”
The LinkedIn B2B Institute’s work on creativity — particularly the evidence that creative quality is one of the most undervalued performance variables in B2B advertising — lands in the same place. The instinct to produce more, faster, at lower cost runs directly counter to what the data shows actually drives long-term brand equity and commercial outcomes.
The buyer doesn’t know enough about a space to know what questions to ask. They use an AI model to build a mental model of the category before they engage with any vendor content directly.
Once the buyer understands the category, they ask the model to help them identify the leading players — and the key differentiators between them. The model’s answer shapes the initial shortlist.
Later in the process, buyers use AI tools to synthesize large volumes of vendor content, analyst reports, and third-party commentary into a comparative view.
At every stage, the AI model is drawing on a corpus of content it has been trained on, retrieved in real-time, or both. The companies whose thinking, expertise, and perspective is most thoroughly represented in that corpus have a structural advantage — regardless of how their website ranks on traditional search.
The companies whose thinking is most thoroughly represented in the AI corpus have a structural advantage. This is not the same thing as ranking well on Google — and conflating the two is costing B2B marketers visibility they don’t know they’re losing.
None of this is an argument against AI. It’s an argument for sequencing.
The temptation in a world of instant generation is to start with the output — to prompt first and think second. But, an LLM can only work with what you give it. It doesn’t know your customer’s unexpressed doubts. It hasn’t lived in the category and doesn’t know the specific moment in a buying journey when credibility is won or lost. It doesn’t know which frame or slide will make a skeptical CFO lean in versus check out.
That knowledge has to come first. And delivering it requires the unglamorous, time-consuming and human work of actually understanding your customers — the problem you solve, the context it lives in, and the human beings on the other side of every piece of communication you produce.
So, before you hand the work to the model: take a beat. Talk to customers. Build the brief. Get the strategy right.
Then, by all means, use every tool available to execute it well.
If you’re a marketer working inside a skeptical, engineering-led organization, you have both a responsibility and an opportunity right now. The AI moment has given you a new reason to make an old argument — that the invisible infrastructure of brand, narrative, and behavioral insight is not decoration. It is what makes everything else work better.
Make the case. Use the research. Rory Sutherland’s Alchemy is a useful starting point for anyone who needs a rigorous, entertaining argument for why irrational-seeming things are often the most rational choices available.
The founders who get this — who understand that human psychology is not a soft consideration — tend to build companies that compound. Those who skip it eventually wonder why the engine isn’t performing the way it should.
The gas was cheap. That was the problem.
Suggested reading
25+ years leading B2B programs for Mastercard, FedEx, and numerous tech scale-ups. PRWeek 40 Under 40. Juan advises investors and leadership teams on marketing strategy, GTM alignment, and the emerging discipline of Generative Engine Optimization for B2B technology companies.
Thinking about your GEO strategy? JTS Advisory helps B2B fintech companies build the content infrastructure that earns AI citation.
