Can You Actually Boost Traffic with AI Content?
I got a message notification on my LinkedIn account.
I opened it, expecting yet another university promotion ad. However, this was different: it was from a SaaS founder who had been following my LinkedIn posts and was interested in a potential collaboration.
We quickly exchanged contacts and scheduled a call a few days later. He sought support in developing a solid content strategy for his brand, which I was ready to take on. Here’s the twist: he wanted me to leverage AI to create the content.
And his reasons were genuine. He:
- Had a tight budget.
- Wanted to mass-produce content.
- Wanted quick results from content marketing.
This was a new type of request, as I hadn’t been a strong advocate for AI-generated content. Fortunately — or perhaps unfortunately — another project came up, so I politely declined the offer.
This is a common scenario for many businesses. Maybe your content marketing budget is tight, and you can’t hire a content team. Or you’ve seen competitors using AI content, and you feel like you’re left out.
As a content marketer who’s been on both sides, I’d love to delve into this topic and give you credible insights to help you decide whether to embrace AI-generated content or approach it with caution.
Let’s start with the basics.
What’s Behind the AI Hype?
If you’ve been keen, every company is becoming AI-powered. For example, Hubspot, which offers many marketing tools, now calls itself the “AI-powered customer platform.”
In addition, funding for AI startups has skyrocketed in the past year. The amount of capital toward AI companies has increased 8 times in one year, reaching $25.2 billion in December 2023. Also, the global AI market is expected to hit $1.81 trillion by 2030.
The excitement around AI is creating a sense of FOMO for many brands. Every CEO wants their product team to incorporate AI capabilities to stay on trend.
But these steps have adverse effects. Liza Adams says, “Building AI wrappers around products feels like standing on melting ice.”
This is achievable because many generative AI models are open source, allowing any brand to integrate AI capabilities into their features.
While AI integration is gaining traction on the product side, its use in marketing has been debated for some time. According to the State of Content Marketing survey, 61% of the respondents have a positive sentiment of AI in the next five years.
This positivity makes brands want to test out AI content. Not to mention that when AI made headlines, some budget-strict CEOs saw this as an opportunity to cut their marketing costs.
Recall the CEO who wanted to work with me. He argued that he was seeking a cost-effective solution, aiming to achieve the output of a whole content team by strategically leveraging AI. There’s pushback from marketing folks, but reaching a middle ground might take some time.
I asked Sara Taher why there’s so much hype around AI, and here’s what she had to say.
The Place of AI in Content Marketing
According to the State of Content Marketing report, about 60% of content marketers are concerned that AI-generated content can capture and convey their brand’s unique voice to their target audience.
This resonates with what Matt Laybourn, Founder & CMO of Rockee.io, says.
However, this doesn’t mean we should dismiss AI entirely. AI still holds a place in the heart of content marketing. Let’s explore some effective ways you can integrate AI into your strategy.
Creating Content Outlines and Briefs
Creating content is hard. If there’s a tool that can simplify your process, why not take advantage of it? That’s where a content outline comes in. It’s the rough skeleton you use to create an article.
An average blog post takes four hours to produce. While that might seem manageable, content marketers aiming to create impactful content know it starts with a solid blueprint.
If there’s one thing AI is good at, it’s creating content outlines. I had a rough idea when brainstorming this article, but it needed more structure.
I posted this prompt on ChatGPT: “Create a content outline for an article titled “Can you Boost Your Business with AI content?”
The model provided a solid outline that filled in the gaps and insights I wouldn’t have gained relying solely on my knowledge.
Rewriting and Editing
One of the main challenges a writer faces is narrowing down a tone that a client wants. For example, the B2B audience is technical and one of the most nuanced.
They don’t consume every blog post they come across, and they’ll notice it’s not well-written right from the introduction.
As a writer who creates content in this space, I faced a similar challenge until I started using ChatGPT to rewrite my sentences.
My prompt is simple: “Rewrite the sentence below so it sounds natural and straightforward in a way that resonates with the B2B audience.” Here’s an example.
As you can see, the result is more refined and adds some punch. This approach doesn’t give the AI full autonomy. It’s a blend of both, allowing you to edit the content and retain that essential human touch.
The best part? Your article won’t be flagged down as AI-generated if you use it to rewrite some sections of your piece.
ChatGPT and Claude are also good editors. Once you’ve finished an article, you can run it through these models to polish your work, catching simple grammar and spelling errors.
Content Research and Topic Generation
AI is very useful when you run out of blog ideas or don’t know where to get new insights.
With the first use case, open ChatGPT and ask it for topic ideas. Make sure the prompt is unique and precise to get the best responses. If possible, share more details about your company and content marketing goals. Below is an example.
If you’ve tried Google, Reddit, or even Quora for content research but aren’t satisfied with the results, you can use Perplexity AI.
It works differently from Google. While Google pulls results from billions of web pages, Perplexity ranks these sources based on relevance to your question. Then, it uses an AI model to synthesize a concise answer from the most relevant sources.
Perplexity AI’s answers are real-time, hence more accurate than ChatGPT and Claude. Here’s an example of the results I got when I entered the topic of this article.
Image Creation
Blogs with images get 94% more views than those without. AI image-generation tools can be used by marketers who want to incorporate AI in their content creation cycle.
You can’t compare the output to what an experienced human graphic designer will create, but it’s enough to move the needle.
Standard AI image generators include DALL-E2, Jasper Art, Night Cafe, Photosonic, and Midjourney.
When You Shouldn’t Use AI
When AI emerged, most content marketers didn’t pay much attention to it. Some dismissed it as a passing trend that would fade before anyone noticed.
In this 2020 article by Dianne Christie before AI became a household name, she suggests that AI might be more hype than reality for many marketers.
Marketers may agree that we’ve been proven wrong based on the new developments we’ve seen. As a result, some go all in on AI-generated content.
That’s where the misconception lies. Thinking that mass-producing AI-generated content will automatically drive ROI is unrealistic.
The reason isn’t that AI-generated content doesn’t perform. Tanaaz Khan, a Content strategist and writer for B2B SaaS brands, shares similar sentiments.
She continues to say, “The real value is not in generating random paragraphs but in turning your ideas into 50% drafts that you can refine further. This requires a lot of experimentation AND internal data. That means you still have to do a lot of work upfront and before publishing to get it into shape.”
Getting content into shape means winning the attention span, which content marketers have battled for years.
Some have advocated for short-form content, others for long-form content (like the skyscraper technique), and others for diversifying content types. While some strategies have proven effective, most have fallen short.
Either way, we can agree that the permanent solution isn’t mass-producing content using AI models. Three reasons:
1. AI Content is Robotic
“In the ever-evolving digital landscape” is the buzz phrase common in the intro of AI-generated content.
You sign up for this type of content when you plug topics on AI tools and mass-produce blog posts. The thing is that AI doesn’t create content with a human touch. It feels robotic, lifeless, and empty. Liam Carnahan agrees with this.
Humanizing your content sounds promising, but it often falls short in practice.
Either you’ll end up rewriting everything, which is time-consuming, or settle for low-quality content that doesn’t measure up to the competition.
2. It Doesn’t Show Expertise
Google introduced the EEAT quality rater guideline in 2022 to ensure that all content produced has a degree of experience, such as having actually used a product, visited a place, or communicated what a person experienced.
This approach immediately dismisses AI-generated content, but Google hasn’t banned it. They’ve clarified that AI content can still rank well if it aligns with their EEAT guidelines — Expertise, Experience, Authoritativeness, and Trustworthiness.
Regardless of this statement, we can all agree that AI content doesn’t qualify for Google’s EEAT status. It’s like shooting yourself in the foot, as you’ll not drive traffic to your sites with AI content.
Search engine results pages (SERPs) are incredibly competitive. Your content must offer unique insights or a fresh perspective on information to stand out. The issue with AI-generated content is that it lacks original insights — AI tools can’t produce new viewpoints, so they often recycle existing information.
3. It’s Not Sustainable
If you’re active in content marketing conversations online, you must have heard about the “SEO heist” Jake Ward did.
Jake successfully used AI to steal 2.3 million traffic from a competitor. He started by exporting a competitor’s site map to gather all their URLs.
He generated topic ideas from that list and created 1,800 articles, ultimately drawing 2.3 million visitors away from the competitor over the next 16 months.
Now, this might look cool. Every marketer aims to make big moves without spending much of the marketing budget.
What happened next was unexpected. After successfully pulling off this strategy and using AI to generate blog posts, the site saw a significant drop in traffic just 4–6 months later. Google hit the site hard, and the traffic plummeted, erasing the results of nearly two years of work.
While the tactic worked and created a buzz in the SEO community, Google clapped back with a site-wide quality check that saw the site lose its traffic.
I’m not saying this to discredit Jake — I’ve worked under him as a writer in his marketing agency, Content Growth, and he’s genuinely skilled at SEO. He has a knack for uncovering strategies that drive results.
However, relying heavily on AI-generated content is risky. It might deliver short-term gains, but eventually, the consequences catch up. When Google starts flagging low-quality content in bulk, it’s only a matter of time before they respond.
What’s the Way Forward?
The debate is still raging.
Proponents of AI argue that it’s all about boosting efficiency. At the same time, opponents contend that AI-generated content struggles to compete in the tough SERP ranking game and fails to drive customer acquisition.
Ultimately, ask yourself this: Do you want to be more efficient or effective in your marketing efforts?
Efficiency means producing a high volume quickly, while effectiveness often requires more time and investment, leading to bigger, lasting results.
Even better? Integrate the two. Use AI to supplement your content marketing goals, but don’t over-rely on it.
