I Used AI to Write 100 Blog Posts — Here’s What Happened

In early 2024 I decided to run an experiment that I was fairly sure would fail. I wanted to see if I could use AI to write a hundred blog posts in thirty days and get measurable traffic from them. Not great traffic — any traffic at all. I had read all the warnings about AI content being penalized by Google’s updates. I had seen the low-quality AI-generated blogs that ranked for a week and then vanished from search results entirely. But I had also watched the tools improve dramatically over the previous year, and I wanted to test the real limits rather than relying on what other people were saying.

The Setup

I used ChatGPT-4 to generate first drafts, then spent fifteen to twenty minutes per article rewriting, fact-checking, adding personal examples, and improving the structure. The full workflow was: research the topic by reading the top Google results and a few Reddit threads (ten minutes), generate a 1,500-word draft with ChatGPT (two minutes), manually rewrite and enhance the content (fifteen minutes), add a featured image from free stock photo sites (five minutes), and publish with proper SEO metadata. Total time per article was about thirty minutes.

I published three to four articles per day across three different sites in three different niches. The quality varied significantly depending on how much I edited the AI output. Articles where I rewrote more than 60 percent of the content — adding specific data points, personal stories, and original analysis — performed measurably better than articles where I made only light edits. The best performers were the ones where you could not tell AI was involved at all. The worst were the ones that sounded like generic corporate blog posts.

Results After Six Months

Here is the data. A hundred articles published. Twenty-eight of them — roughly a quarter — generate about 80 percent of the total traffic, which settled at around twelve thousand monthly visits across all three sites combined. The other seventy-two articles generate almost nothing. A few visitors here and there, but nothing meaningful.

The successful articles average about 1,800 words and rank for fifteen to twenty-five long-tail keywords each. They are comprehensive, specific, and include original insights. The failed articles average about 800 words and rank for one or two keywords that almost nobody searches for. They are generic and forgettable.

Google did not penalize any of the sites for using AI. I spent a lot of time checking for signs of a penalty — traffic drops, ranking losses, manual action notifications in Search Console. None of that happened. I could not find any correlation between whether an article was AI-assisted and how it ranked. The ranking factor was not how the content was created. It was whether the content was genuinely useful to the person reading it.

What I Learned

AI is good at some things and bad at others. It is good at summarizing research, creating outlines, and generating first drafts quickly. It is bad at original insights, personal stories, and nuanced opinions that require real experience. The articles that worked were the ones where I used AI to speed up the process but added my own perspective and experience. The seventy-two that failed were the ones where I trusted the AI too much and did not add enough of myself.

The lesson is straightforward. Use AI for speed. Use your own experience for substance. The combination of both is powerful. Either one alone is not enough.

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