How To Blend Ai And Human Input In Your Content Approach

No, you can’t just trust AI to do your SEO work for you.

Great SEO requires smart humans. 

But used strategically, it can be an effective accelerant for great organic growth.

In other words, as I recently explained to a client, simply using AI to mass-produce content doesn’t work – but a structured AI-driven workflow does. 

When I say “work”, I mean: 

• It works for the client by delivering results.
• It works for me because it helps us operate more efficiently and take on more client work with the same number of employees.

Before the process I’m about to lay out, I used to have to hire a team of writers for client content initiatives. 

Now, I can scale content with a couple of really good SEO and content managers, and those folks can work much faster in helping our clients achieve their growth goals.

Now for the process.

Build a custom GPT for each client (starting with ChatGPT)

GPT stands for generative pre-trained transformer, a type of large language model (LLM) and a prominent framework for generative artificial intelligence. 

It is an artificial neural network that is used in natural language processing by machines.

In the client-onboarding phase, we build each client a custom GPT that uses ChatGPT as the LLM foundation. 

(Note: We continually test different LLMs, including Gemini, DeepSeek, Claude, Anthropic, etc., for quality, relevance, and speed, but we usually come back to ChatGPT.) 

That GPT operates as the centralized knowledge base and training center for that specific brand/industry. 

Then, we input all the onboarding data we can obtain from the client to train the GPT on key marketing components like:

• Target personas.
• Brand voice and style guidelines.
• Customer testimonials.
• Industry research.
• Competitor content.
• Target keywords.
• Etc.

This way, we have a good working model that we can continue to train as we produce content. 

Move into a four-stage production phase

In the production phase, our content AI workflow follows four key steps, designed to maximize our human-in-the-loop inputs while leveraging AI strengths of speed and scale:

• Keyword and topic research.
• Content structuring and drafting.
• Content personalization and repurposing.
• Performance tracking and continuous optimization.

Let’s get into the details of each stage.

1. Keyword and topic research: AI as an ideation engine

Great keyword and topic research starts with understanding the humans involved. 

For agencies, this means understanding the client’s business goals and the needs and desires of the client’s audience segments. 

In other words, SEO humans come first (and last) at this stage.

We use AI to achieve two things at the research stage: 

• Rapidly analyze search trends, competitor content, and keyword gaps to identify high-potential content opportunities.
• Cluster related search queries and suggest content angles based on user intent.

From there, we use our understanding of the client’s business goals and their audience’s needs to validate the AI-generated keywords using:

• SEO tools (Google Search Console, Google Keyword Planner, Ahrefs).
• Manual research. 

We then prioritize keyword clusters based on competition, search volume, and strategic goals to chart our path in stage two.

2. Content structuring and drafting: AI as a speedbooster

Ever noticed that it’s harder to start from a blank page than it is to edit someone else’s work? 

AI comes in extremely handy here. 

We use AI to generate content briefs by analyzing top-ranking pages, suggesting subheadings, FAQs, and key points. 

For long-form content, we use AI to produce first drafts that provide structure and flow, reducing the time spent on blank-page writing.

From there, the humans take over. 

Our team enhances AI drafts with:

• Brand voice.
• Storytelling.
• Unique insights.
• Originality.
• Expert validation (so you don’t get hallucinations or recommendations to eat a rock a day).

Dig deeper: The art of AI-enhanced content: 8 ways to keep human creativity front and center

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3. Content personalization and repurposing: AI for scalability

One big bugaboo of SEO and content teams in every industry is the failure to deploy a content theme in every available package. 

AI helps repackage content into multiple formats, such as turning a blog post into:

• Email snippets.
• Social media posts.
• Video scripts.
• Part one of a larger industry guide.
• Etc.

AI-powered summaries can also extract key takeaways and generate different versions tailored to various audience segments – perfect for, say, a blog post like “The {Audience Segment}’s CliffsNotes from {Big Signature Piece of Content}”.

AI truly shines in the remixing and repurposing stage (that’s what it does, after all), but even here, people play an important role to ensure that:

• Messaging is consistent.
• The content is aligned with (and promoted according to) broader marketing goals.

4. Performance tracking and continuous optimization

To truly maximize AI’s impact in this process, we use it to identify patterns and provide distilled insights for reporting and continuous optimization.

AI automates pattern recognition in traffic trends, ranking fluctuations, and user behavior, which is great insight for us to process as a team and deliver to clients. 

AI-generated performance summaries are also highly useful in producing actionable insights out of complex data sets. 

My team’s role is to interpret those insights and adjust our content strategy accordingly, by iterating on the next round of content ideas of editing/optimizing existing content, or both. 

As business partners, we also provide our clients with context and business relevance beyond AI’s raw data so they understand the significance of the numbers and where we go from there.

Why this process works for us

Best practices are always a moving target, especially with tools evolving as rapidly as they are in the GPT/LLM space. 

But as I write, this process accomplishes three key things for us and our clients: 

• Scales content production without sacrificing quality.
• Uses AI where it excels (automation, synthesis, and efficiency).
• Keeps human experience where it matters (strategy, originality, and brand differentiation).

Dig deeper: Want to beat AI Overviews? Produce unmistakably human content