How To Use AI for SEO Content Writing (Without Breaking Quality)

It’s no secret that a lot of people are using AI to mass-create garbage and put it on the internet today.

I think one Reddit user put it perfectly, saying search results feel “rotten, mass-generated, and empty.”

There's a real gap between production and value. While an impressive 71% of marketers using AI say their content marketing is effective, a lot of readers feel differently.

But the truth is, there are still plenty of us using it to get results faster and cheaper, without adding to the crap online.

So, in this article, I want to focus on how you can use AI to be more efficient and effective — from my 10+ years of experience in content marketing.

My goal is to help you get your time back for strategy and creativity while still making high-quality content that actually helps your audience.

To do that, we’ll walk through a framework I use that’s all about a human-led mindset, specialized tools, and a process that values context over just prompting so you can use these tools without losing your mind.

Key highlights

A human-led mindset is step one: The first and most crucial step is a simple decision not to use AI mindlessly. Your success depends on a human-led approach that infuses your unique expertise and point of view (POV) at every stage, not just during final edits.
Focus on the process, not just the prompt: I've found that effective AI content isn't just about writing a good prompt. Quality really depends on the AI tool's underlying process and its ability to consistently apply your context, research, and brand voice throughout the entire piece.
Put your human expertise in first: Instead of using AI only first and relying on a heavy human review at the end, which I see as "putting the cart before the horse," focus on a human-led process upfront. The more strategic input you provide before generation, the less editing you'll have to do later.
Use specialized tools for specialized jobs: My advice is to avoid the "one tool for everything" trap. Use specialized AI tools for specific functions, like one for keyword research and another for long-form content creation. All-in-one tools often let a key function suffer.
Aim for "T-shaped" content: I define high-quality AI content as "T-shaped." It must provide genuine value to the audience (the horizontal bar of the T) while simultaneously achieving your specific marketing objectives (the vertical bar of the T).
Google cares about quality, not origin: Google doesn't penalize AI-generated content; it penalizes unhelpful spam. The key is using AI to create helpful content, not to mass-produce low-quality articles that don't serve searchers.

Now that we’ve covered the big picture, let’s get into the practical side. Here’s my 4-step framework for putting a human-led approach into action.

Step 1: commit to a human-led process, not AI-led

Before you even think about which tool to use, the first step is a mindset shift.

It starts with a simple decision: don’t use AI mindlessly. Treat it as a collaborator that amplifies your thinking, not something that replaces it.

The goal is to create content built on your genuine experience and unique points of view (POVs), not just another piece of generic AI slop. For me, this means I refuse to use any AI content tool that doesn't give me the flexibility to infuse my POVs at multiple points in the creation process.

I’d only use tools that take an "anti-slop" approach by essentially capturing my POVs and direction before writing any text.

This ensures I lead the process and the final output is mine. It’s like how one marketer on Reddit put it: they use AI as a tool to speed up work, not to replace it.

The biggest pitfall I see many content folks make is accepting a "one-shot" creation process, where you give the AI a topic and it spits out a full draft without any checkpoints.

This approach is dangerous because it neglects your expertise. If I'm writing a guide on launching a SaaS business, for example, I have specific experiences I want to include, and a one-shot tool would just ignore all of that.

By keeping your hands on the wheel with this human-led approach, you make sure you’re not just using AI to get faster, but to get better.

Step 2: Build a toolkit of specialized AI apps

A common thing I hear from marketers is the search for a single AI tool that does everything.

While it sounds efficient, my experience shows that when a tool tries to handle everything from keyword research to long-form content, something usually suffers.

This is how you get compromised quality. Instead, I recommend building a "toolkit" of specialized apps. Audit your content workflow and find those distinct, repeatable tasks. It could be something simple but time-consuming.

For instance, I saw a marketer on Reddit mention they use AI to quickly generate SEO-optimized alt text for images. That's a perfect micro-task for a specialized tool.

A high-quality workflow might involve using Ahrefs for keyword research and a platform like Leaps to create long-form, expert-led SEO articles.

The biggest pitfall to avoid is over-relying on foundational models like ChatGPT or Claude for every single content function.

It’s a major misconception that these tools can handle every specialized task. They weren't built for the nuances of high-quality content creation, and forcing them into that role is often what leads to subpar results.

Step 3: Prioritize context integrity over prompt engineering

From my experience, this is where a lot of marketers miss the mark with AI. Everyone focuses on "prompt engineering," but giving detailed prompts is the easy part.

The hard part is getting an AI tool to actually use that context consistently, especially with long-form SEO content.

When a tool can't hold onto your POVs, research, and brand tone from one section to the next, you end up with the generic AI slop we all want to avoid.

The solution isn't a better prompt; it's a better process. I recommend an "anti-AI slop" workflow where you lock in your unique perspectives and key data points before the AI starts writing.

This means choosing tools like Leaps that are designed to carry your context through the entire article.

The biggest mistake I see is people obsessing over crafting one perfect, massive prompt, thinking it will solve everything. It won't. This is often a tool limitation, not a user error. It's a huge problem. I saw one Reddit user point out that brand drift is a real issue with AI content, and that’s because the process needs human guardrails to prevent it.

Step 4: Shift human involvement upfront to minimize final edits

This next step is all about restructuring your workflow to be human-led from the start.

Like I said before, relying on a final human review to fix fundamental issues is like putting the cart before the horse. It's a reactive process that tries to salvage a first draft that might be completely misaligned with your strategy.

Instead, the goal is to get the AI aligned from the very beginning. Your first draft should only need a light polish, not a major rewrite.

The principle I follow is simple: the more work you do up front, the less work you do at the end. Reallocate your time from heavy back-end editing to front-end strategic direction.

Use your expertise to "twist and turn" the AI before it even starts writing by infusing your specific POVs, client data, and brand voice into the brief.

For example, you can collaborate with the AI section-by-section to define the core arguments before the draft is written.

The biggest pitfall I see is what I call the "peek-a-boo" approach, where you feed the AI a vague prompt, wait to see what it produces, and then try to fix everything in post-production.

This is incredibly inefficient. A much better workflow uses AI to speed up ideation and first drafts, while you ensure consistency and brand alignment from the start.

What high-quality AI content really means (hint: it’s not about the prompt)

True quality comes from the process you use from the start. From my experience, it has three non-negotiable traits.

1) It serves two masters: the reader and the business

First off, I define high-quality content as "T-shaped content."

The horizontal bar of the 'T' is the value it provides to your audience, answering their questions completely and genuinely.

The vertical bar is the value it delivers for your business, because let's be honest, SEO content is marketing, not literature. It has to serve a business objective.

This is where I see a lot of AI-driven strategies go wrong. They get so focused on speed that they forget about strategy.

But when you only focus on speed, you end up with content that feels empty and fails to serve the reader or the business.

2) It's built on verifiable accuracy, not AI hallucinations

Trust is the foundation of good content, and you can't build it on shaky ground.

It’s wild to me that some people rely on an AI to generate text and then ask a human to verify every single claim. That’s an almost impossible job. Personally, I won’t use tools that don't have safeguards for accuracy built-in.

The risks here are huge. One scientific paper from PMC found that in a test, only 8% of the sources an AI cited were even real. That's a massive problem.

It's why I believe the right approach is to use tools that incorporate fact-checked research and primary data before the AI even starts writing. This solves the trust issue at its source.

3) It amplifies a human Point of View (POV), it doesn't replace it

The single biggest difference between useful content and "AI slop" is a unique, human perspective.

Your expertise, your experience, and your brand's voice are your competitive advantages. And a good AI tool shouldn't replace that; it should amplify it.

That's why so many people get frustrated. It's like that Reddit user I brought up before said: brand drift with AI is a real problem. That drift happens when you let the AI take the wheel.

I believe in a human-led, anti-slop process where the tool works with you, section by section, to get your insights into the article. It's the only way I've seen AI consistently produce content that’s actually original and valuable.

Why some AI articles fail to rank

There's a lot of confusion out there about AI and SEO. The truth is, Google doesn't care if you use AI. It cares if you create helpful, high-quality content. So the problem isn't the tool; it's the strategy. When I see AI content fail to rank, it almost always comes down to a few core reasons.

Reason 1: You're creating "AI Slop," not AI-assisted content

First, we have to make a clear distinction between "AI-generated" content and "spam." AI itself isn't what gets you penalized; it's the tactic of mass-producing unhelpful, low-value pages. It’s a mindless approach that replaces strategy with volume.

The difference is stark. There’s a great example of this in the TailRide case study, where a site that published thousands of AI articles saw its traffic drop to zero because Google decided they offered no “genuine value.”

Contrast that with an Ahrefs study of 600,000 pages that found zero link between AI use and search rankings. The takeaway is clear: Google penalizes unhelpful content, not the tool used to create it.

Reason 2: The content lacks expertise, authority, and trust (E-E-A-T)

A lot of generic AI content fails because it completely misses the mark on Google's E-E-A-T guidelines.

It lacks Experience because, well, AI has none. It also often lacks Expertise and Trustworthiness because it can't distinguish between fact and fiction, leading to inaccuracies and hallucinated sources.

From my perspective, this failure comes from a process that relies on generic advice and lacks verifiable citations.

It's the kind of content that doesn't have a real point of view. To rank, you need to infuse your content with genuine expertise and trustworthy information, which means using a process that prioritizes your human insights from the start.

Reason 3: It fails to meet real user intent and lacks a unique POV

Many AI tools are great at one thing: recognizing patterns and summarizing what's already on the internet.

This is also their biggest trap. So if you just ask AI to write an article, it will often just rehash what's already ranking, creating a slightly reworded version of existing content without adding any new value.

The goal shouldn't be to replicate the SERPs faster. It should be to add your unique layer of value on top. The more work you do upfront to define your POV, the less generic your final content will be.

1) Prioritize specialized tools over generalist platforms

The "one tool to rule them all" mindset is a major pitfall.

A platform that's amazing at keyword research, like Ahrefs, isn't what you'd turn to for creating high-quality, long-form content. And a generalist chatbot wasn't specifically built for the nuances of SEO content creation.

I think this mismatch is a big reason why research from BCG shows 74% of companies struggle to get real value from AI. Using a generalist model for a specialist's task often leads to the generic "AI slop" we all want to avoid.

You get much better results by choosing tools that are purpose-built for the specific job you need them to do.

2) Evaluate tools on their ability to amplify human expertise

I keep saying this, but it’s true: the best AI tools don't try to replace you; they act as your co-pilot.

So when you're evaluating a tool, the most important thing to look for is a human-led workflow. I Instead, look for tools that let you twist and turn the AI, infusing your unique POVs, research, and brand voice at multiple points in the process.

This approach is the only way to prevent brand drift and ensure the final output reflects your expertise. The more work you do upfront to guide the AI, the less you have to fix on the back end.

3) Explore top-tier platforms built for specific SEO goals

With so many marketers using AI, a number of specialized, high-quality platforms have emerged.

Instead of trying to find one tool for everything, I recommend building a small stack of tools that excel at their specific functions. Here are a few tools I've seen that are built around this idea:

Leaps: This is the anti-AI slop writer. It helps you create original, expert-led SEO content by combining human thinking with accurate research from the start. It’s ideal if your main priority is maintaining quality and a unique point of view.
Writesonic: I see this as a strong option for AI-powered SEO and content automation. It also focuses on tracking and improving your brand's visibility in new AI search environments, making it a good fit for teams focused on automation and performance.
Writer: This is the go-to for large organizations. It's an enterprise AI platform for teams that need secure, scalable, and on-brand content that's tied directly to their own internal data.

We’ve covered several other AI content writing tools in these articles, so check them out:

Let's tackle a few common questions I hear all the time. These are the things that can trip you up if you don't have the right mindset from the start.

Can Google detect AI-generated content and penalize my site?

This is a big one, but the answer is pretty straightforward. Google's main focus is on penalizing spam and unhelpful content, not content simply because AI was involved in making it.

The real distinction is about quality and value. As long as what you publish is original, helpful, and actually answers the searcher's question, it doesn't matter what tools you used.

Is learning "prompt engineering" the most important skill for getting quality results?

In my experience, not really. While giving detailed prompts is the easy part, I’ve found that the bigger problem is that most AI tools just can't consistently hold onto the context you give them, especially for long-form content.

This isn't a prompt problem; it's often a tool problem. The solution is to use a tool designed to carry your unique POVs and research through every single section.

Do I need a special tool for SEO content, or is ChatGPT enough?

I’ve seen this lead to a lot of frustration. Relying on general models like ChatGPT for a specialized task like SEO content creation is tough because they weren't built specifically for that job.

I believe you get the best results when you use tools that specialize. You use Ahrefs for keyword research, and you should use a dedicated content creation platform like Leaps for writing. When a tool tries to do everything, something usually suffers.

How do I maintain my brand voice and unique perspective when using AI?

The key is to adopt a human-led approach from the very beginning. I’d never use any tool that asks me for a topic and just generates a draft, leaving me to fix it later.

Instead, you should use tools that let you infuse your points of view, research, and brand context before the AI even starts writing. The more strategic work you do upfront, the less editing you'll have to do at the end.

Embrace AI as a collaborator, not an autopilot

It’s no secret that AI has enabled a lot of low-quality content.

So the goal isn't to add to that noise. It’s to use AI as a powerful assistant that makes your human expertise more efficient and effective.

When you shift your mindset from replacement to collaboration, you reclaim time to focus on what truly matters: strategy, creativity, and producing high-quality content that actually serves your audience.

This is how you become part of the solution, not the problem.

So the first step I want you to take is simple: make a firm decision not to use AI mindlessly.

Evaluate your current process and find where you can inject more of your strategy and perspective upfront.

This human-led approach is exactly why I built Leaps. It’s an anti-AI slop content creation tool designed to amplify your thinking with AI, not replace it, ensuring your POVs and accurate research are the foundation of every piece of content.

It all comes back to a simple truth: the more work you do up front, the less work you do at the end.