You're Making AI Content Like Everyone Else (Here's Why It Doesn't Work)

2026-07-23 — marketing implementation consulting

A client's content looks exactly like their competitor's. Yours probably does too.

This isn't an accident. It's the structure of how AI works.

When Gabriel Dillon from Contentful laid out why AI-generated copy has stopped converting, he pointed to one brutal fact: 68% of Google searches now end without a click to any website. That means the game everyone was playing—pump out more content, rank higher, get traffic—has already ended. The game just hasn't fully acknowledged it yet.

The problem is your biases.

You write a prompt. ChatGPT mirrors what you already believe, or worse, mirrors what every other brand wrote into their tool's training data. The output comes back sounding "good"—structured, polished, confident—and reads exactly like the thing your competitor published last week. Gartner found that 49% of consumers now believe AI content quality is declining, not because the AI got worse, but because the internet flooded with the same three arguments about the same problem, dressed up in slightly different paragraph order.

87 marketers in a recent survey said their biggest concern is that AI-generated content feels thin or generic-sounding. They're not complaining about the tool. They're watching their own output blend into the noise.

Volume was never the real strategy anyway.

Actually, I'm not sure that's quite right—volume *was* the strategy, for about eight months. Some brands did get lucky: publish fast, catch a trend, rank before competitors can react. That window has closed. Salesforce's 2026 data showed that retailers using AI-powered personalization saw customer satisfaction improve by 31%, while those just publishing more content without a perspective watched engagement flat-line.

The shift requires three things most content teams skip.

First, accountability to actual outcomes, not rankings. You're not publishing for the algorithm. You're publishing for a specific person who's trying to solve a specific problem. Dillon's counterweight is taste: discernment and intuition, plus the risk-taking to make a claim no AI tool would volunteer, based on what you actually know. A tool can't take a risk. It can't lean into what makes your company different. It can't care whether the content actually moves someone closer to a decision.

Second, data that traces back to real behavior. Not impressions. Not sessions. Clicks, conversions, time-to-decision, customer feedback. Did someone actually use this? Did they tell a friend? The biggest gap most teams miss is that generation speed and production speed are not the same thing. You can generate a draft in seconds. Getting it to the quality your audience expects—that takes editorial judgment, fact-checking, and rewriting. The AI handled the easy part.

Third, distribution that reaches the people who need to find it. Named authorship and entity clarity function as crawlable trust signals for both humans and LLMs. Anonymous AI-generated content gets deprioritized by search engines and ignored by readers. Content with a real human's name, credentials, and publishing history doesn't.

The consulting industry got this wrong too.

We saw early success with AI, shipped more AI-assisted content, and watched our own engagement drop. Then we started asking what was different about the pieces that actually got shared. Every time: they had a point of view. They said something that contradicted conventional wisdom. They were written by someone who could defend it. You can't delegate that to a model.

What's worth trying instead. Use AI as a research acceleration tool. Fact-checking layer. Draft generator. Then replace the generic parts with your actual experience. Companies that have fully embraced personalization strategies powered by AI have seen a 10% or more increase in sales. Not from more volume. From content that reflects real customer needs, delivered to the right person at the right time.

The brands winning right now are the ones who treat AI like editing software, not replacement staff.