You’ve seen the claims.
“Write 10 blogs in 10 minutes!”
“Let AI handle all your content needs!”
It all sounds great until you actually read the results.
AI-generated content is everywhere. Some of it’s decent but a lot of it isn’t. And if you’re trying to build a brand people trust, you can’t afford to hand over the reins to a robot. But you also don’t have to ignore the tech altogether. AI can’t replace human creativity but it can support it.
So, should you use AI-generated content or lose it completely? The answer isn’t black and white. It depends on how you use it, what your goals are, and whether you’re willing to stay in the driver’s seat.
Let’s break it down.
Quick Takeaways
- AI-generated content can speed up workflows but can’t replace human creativity.
- Use AI for brainstorming, outlining, and repurposing, not for thought leadership or brand storytelling.
- Overreliance on AI risks producing generic, inaccurate, or low-value content.
- Always edit and refine AI drafts to reflect your brand’s voice and expertise.
- AI works best as a tool to support your strategy, not as a shortcut around it.
What Is AI-Generated Content?
AI-generated content refers to any content written (fully or partially) by machine learning tools trained on huge datasets of existing text. Tools like ChatGPT, Jasper, Claude, and others can spin up blog posts, emails, video scripts, and even code in seconds.
Marketers often use AI tools to:
- Draft blog post outlines
- Generate product descriptions
- Repurpose long-form content into social posts
- Write ad copy
But the final output depends on two things: the quality of the prompt and the judgment of the person using the tool. AI can mimic tone and structure. It can organize information. What it can’t do is think.
And that’s where human oversight becomes non-negotiable.
Why AI-Generated Content Took Off
AI didn’t explode because everyone suddenly wanted to ditch their writing team. It took off because the pressure to create content keeps growing.
Most marketing teams are:
- Under-resourced
- Chasing deadlines
- Publishing across multiple platforms
- Asked to “do more with less”
To no one’s surprise, use of AI increased significantly in 2024. According to McKinsey, 78% of organizations now use AI in at least one business function, up from 55% the previous year. The tools are there, and teams are using them. Because they have to.
When AI tools offered a faster way to get words on the page, teams jumped on it. Fair enough. No one wants to spend six hours staring at a blinking cursor.
The temptation is real, but speed isn’t a strategy. When everyone starts publishing the same AI-spun content, it stops standing out. What felt like a productivity win quickly turns into more digital noise.
The Pros of Using AI for Content Creation
Let’s be clear: AI has a place in content workflows. Used well, it can help you move faster without compromising quality. But only if you know what to use it for.
Here are a few smart ways to let AI lighten the lift:
1. Idea Generation
AI tools are great for brainstorming. Need 20 title ideas, a fresh metaphor, or a list of subtopics? Done.
2. Content Outlines
Give it a topic, and you’ll get a rough structure in seconds. It’s not always perfect, but it’s a solid starting point, especially if you’re feeling stuck.
3. Content Repurposing
Have a webinar transcript? AI can help shape it into a blog draft, pull out quote cards, or draft a quick recap email.
4. Speeding Up Repetitive Tasks
Think product descriptions, meta tags, or basic summaries. The kind of writing where structure matters more than storytelling.
But none of these tasks should be fully automated and published without review. Every AI draft needs a human gut check.
The Cons and Risks of Relying on AI Too Much
Here’s where things get risky. Rely too heavily on AI and your content starts to sound like everyone else’s. Worse, it might say things that aren’t true, relevant, or aligned with your brand.
1. Generic Voice
AI often defaults to vague language, cliched phrases, and an overly polished tone. It’s writing that looks like writing but says nothing.
2. Inaccuracy and Misinformation
AI doesn’t know facts. It predicts what “sounds right” based on patterns in data. That means it can sound confident while being totally wrong. Buyer beware.
3. SEO Risk
Google doesn’t penalize AI content outright, but it does penalize low-quality content. AI-generated filler content that adds no value is exactly what Google targets.
When to Use AI (And When to Skip It)
AI works best when you treat it like a support tool. Here’s a quick framework to help you decide when to use it and when to rely on human creativity:
Use AI for:
- Brainstorming: headlines, formats, angles
- Research assistance: summarizing articles or extracting key points
- Drafting outlines: speeding up the structure phase
- Content repurposing: breaking long-form into snippets
Avoid AI for:
- Thought leadership: your expertise can’t be automated
- Brand storytelling: voice, tone, nuance matter too much
- Sensitive topics: accuracy and context are everything
- Final drafts: AI can’t make judgment calls
Think of it like this: Use AI to make your process faster, not lazier.
How to Blend AI and Human Creativity the Right Way
There’s a sweet spot here. The smartest teams aren’t avoiding AI. They’re integrating it, but with intention.
Intention also means oversight. Too many teams are letting that part slide. McKinsey reports that only 27% of organizations using generative AI say their employees review all AI-generated content before it goes live. And about the same number say they review less than 20% of it. That gap in oversight is exactly where brand risks and bad content creep in.
Here’s how to do it right:
1. Always Rewrite the Output
Treat AI drafts like raw material, not finished products. That first version is just a placeholder for your expertise. Take the bones and rebuild it using your brand’s tone, voice, and perspective. When you rewrite with purpose, you turn generic content into something worth reading.
2. Inject Strategy
Before you hit “generate,” know what you’re trying to achieve. What’s the audience’s pain point? What stage of the funnel is this for? What CTA needs to land? If you don’t give the tool strategic guardrails, you’re setting yourself up for shallow, unfocused output.
3. Train It on Your Voice
The best AI outputs come from strong inputs. If your tool allows you to feed it sample content or voice guidelines, do it. Teach it your syntax, tone, and vocabulary. A well-trained model can save editing time later and keep your voice consistent across channels.
4. Layer in Your Expertise
Anyone can prompt an AI tool. What makes your content different is you. Add specific examples, stories, or expert insights only your team would know. It’s these human touches that build trust, drive engagement, and elevate good content into great.
5. Review Like an Editor
Don’t just skim it. Scrutinize it. Check for structure, clarity, logic, and tone. Replace weak verbs, cut filler, and if nothing else, cross-check your facts. This is where the real work (and value) happens. Publishing faster is only going to lean in your favor if the content is strong.
Be Choosy, Not Lazy
AI-generated content isn’t going anywhere. The difference between good and bad use comes down to whether you’re leading the content process or outsourcing it entirely.
Let AI help you brainstorm faster, structure smarter, and repurpose more efficiently. Don’t let it replace your voice, your strategy, or your standards.
The best content is written with AI—by real people who know what they’re doing. If you want content that connects, keep the human in the loop.
Want to build a content strategy that uses AI the right way? Learn more about my content strategies, or let’s talk about how I can help you stand out where it counts.