Google doesn't hate AI content — it hates content that teaches you nothing
This one is for my marketing teams, content strategists, and agencies.
Google doesn't care if AI helped create your content. It cares whether your content helps readers.
I've seen both sides of this reality.
While working in the industry, I've watched several publications and company blogs go from millions of monthly views to virtually disappearing from search results overnight. Their common failure? Publishing AI-generated content that answered nothing, taught nothing, and provided no unique insights.
Conversely, when I wrote my post on "How to use ChatGPT's deep research," it secured spot #2 on Google right away in the first week of the tool's launch. I was literally positioned right under OpenAI's own announcement page, resulting in tens of thousands of hits to my newsletter within days.
The kicker? I didn't even think about SEO when writing it.
When you focus on creating valuable content, especially before anyone else, you don't need to obsess over SEO. Google has evolved to where value is inherently what they're looking for.
The fundamental misunderstanding is thinking this is a technical problem when it's actually a value problem. Writers and marketers are wasting time with bad AI content generation instead of focusing on what actually matters – creating content worth reading.
Today's newsletter was inspired by a great question from a member in my Writing Accelerator:
What Google actually penalizes
Google has repeatedly stated they don't penalize AI content specifically. They penalize low-quality content regardless of how it's created.
Three specific patterns consistently trigger penalties:
Content that summarizes other top results without adding new insights
Content optimized for keywords rather than answering real questions
Generic "expert" advice that lacks practical implementation details
Most SEO advice around AI content is based on outdated assumptions about keyword density, content length, and other technical factors. Meanwhile, Google has evolved to prioritize genuine expertise, unique perspectives, and practical value.
Those multi-million view blogs that disappeared didn't fail because they used AI. They failed because they used AI poorly – to create more of the same generic content we've all learned to ignore.
Why a systematic approach matters
Many writers or marketing and content teams approach AI writing backwards. They collect random prompts (maybe not even this), put little thought into the content and project knowledge that needs to be uploaded and referenced, and hope something works. This is like trying to build furniture without a blueprint or even knowing what tools to use when.
The breakthrough comes when you stop thinking about isolated tools and start building systems.
A prompt might help you write a paragraph or outline an article. But a system with loads of hand-picked context helps you:
Research deeply before writing a single word
Verify information against reliable sources
Integrate unique insights your competitors miss
Structure content for both human readers and search algorithms
Create content that genuinely teaches something valuable
In my AI Writing Accelerator course, I teach complete systems. These systems combine multiple AI tools in structured workflows that consistently produce valuable content.
Creating content that both humans and algorithms value
The secret to thriving in the Google AI era is dual optimization – creating content that genuinely helps readers while also giving search algorithms the signals they need.
Here's what this looks like in practice: