AI Content Creation: Where It Helps and Where It Hurts

AI content creation is unavoidable now. If you work in any online space, you’ve seen how quickly it’s become part of everyday workflows, and if you don’t adapt, you can get left behind. The good news is that AI can be a genuinely useful tool for speeding up processes and getting content live faster. The less good news is that if you try to cut too many corners, it can damage performance in the long run, especially when it comes to search and trust.

This is about getting the balance right. Understanding what AI is actually good at, where it causes problems, and how to use it in a way that supports your content rather than accidentally hindering it.

There is a time and a place for AI copy

The first thing to say is that there is a time and a place for AI copy. Like anything, it has strengths and weaknesses, and the quality depends largely on what you’re asking it to produce and how. As a general rule, AI is pretty bad at generating site copy, and it often struggles with long form content too. 

If you are going to use it for long form, it tends to work better for blog posts or articles, but even then, you need to be careful. A big reason for this is that AI likes to frame long-forms like a narrative, or a story. Over time, everything starts to sound the same because it follows the same structure and the same idea of what copy “should” look like. It can be much better for short form copy such as ads or product descriptions, largely because those formats are more factual and rely less on a creative voice. 

But the main limitation is bigger than style. AI cannot replicate the strategy that needs to happen for truly effective copy. It cannot replace the SEO research, keyword thinking, and planning that should happen before you write. That’s why it’s much better used as a supportive tool for creating your own content, rather than generating the final output itself.

The risks and trade-offs of AI-generated content

If you ask AI to generate copy outright, there are a few trade-offs worth taking seriously.

One is accidental plagiarism. It’s not uncommon for models to lift existing copy from other sites. Even if a tool cites sources, it won’t necessarily tell you if it has directly lifted content, and that can cause all sorts of issues, including ranking problems.

Another is a lack of SEO thinking. AI-generated content isn’t naturally created with keywords, content clusters, internal linking, and ranking intent in mind. Without those being factored in properly, you can expect an impact on performance. Even if you include your own keywords and grounding, when AI generates the bulk of your copy, it’s still pulling patterns and phrasing from other sources online.

Then there’s originality, which is often the biggest trade-off. AI-generated copy has a very distinct voice, especially with tools like ChatGPT. Some of the giveaways are frustrating, because as content creators we’ve been taught that certain techniques are good practice. The rule of three is a great example. It’s effective, it helps information stick, and now it’s become a signpost people associate with AI writing. Over time, this sameness can hurt engagement and brand trust, which is why holding on to your individual voice matters so much. Tone of voice is something that AI consistently struggles to capture.

How to spot AI-generated copy

There are some common tells. One of the biggest is the heavy use of em dashes. Excessive listing is another, along with lots of bullet points and numbered lists, overuse of bold and italics, and too many quotation marks. You also often see the rule of three used repeatedly in a short space, plus American English showing up on UK sites.

Beyond formatting, the patterns show up in the writing itself. Lots of short sentences, clichés, and signposting lines that don’t add meaning; things like “let’s dive in”, “it’s not X, it’s Y”, or “the real question is”. And then there’s fluff, where the copy says a lot without really saying anything, sometimes even repeating the same sentence in a slightly different way.

For example, I asked ChatGPT to write a 100 word, spoken introduction to this topic. I ran the exact same prompt through the model twice, only the second time, I added our Spindogs tone of voice document.

In theory, the second should have felt more accurate and personable, but it didn’t. If anything, it came out even worse. The big takeaway from this example is that even with grounding documents, voice is something ChatGPT in particular struggles with. 

There are other AI models, such as Jasper or Copy AI, that specialise in writing content. But with ChatGPT being the biggest free option, it’s what people gravitate towards, and is why everything online right now seems to read the same way.

How search engines treat AI content

Even with AI overviews appearing in Google results, over-reliance on AI-generated content can still negatively affect your rankings. It’s not necessarily an automatic trigger where AI copy gets sensed and demoted, but it does happen through the ways search engines evaluate quality.

The first factor to consider is Google’s search quality rater guidelines. Google uses human evaluators to test the accuracy of its search engine, focusing on the quality of content. Within their guidelines for these evaluators, Google have instructed people to rate AI-generated content as the lowest quality by default since 2025. This means if your content is recognisable as AI generated, you’re likely to be immediately penalised.

Google’s core updates also matter. Recent updates have focused on improving user experience by showing more locally relevant content, reducing sensational content and clickbait, and showing more in-depth, original, and timely content. Original is the key word here. If your content sounds like everything else online, and like everyone else using AI, it’s less likely to be treated as original and trustworthy.

Bing is less strict, but still prioritises content with ‘Quality and Credibility’, which is essentially Bing’s equivalent of Google’s EEAT system. That’s to say, if your copy doesn’t ooze quality and credibility, it’s still not going to rank well.

It could be that the AI chose niche longtail keywords that aren’t actually relevant for ranking, it could be that the tone is obviously AI, and it could also partially be due to external features like the universal slowing of click-through rates since the introduction of AI overviews. 

There’s ultimately nothing wrong with wanting to show up in featured snippets or AI-driven placements, but it’s important to understand the difference between optimising for AI and letting it override what you know about SEO. 

The most important thing is that your content still needs to be primarily readable for human users. Your audience has to stay the priority.

What AI is good for instead

After a lot of what not to do, it’s also worth considering what AI is genuinely good at. The best results come when you use AI as a supporting tool, rather than something that outright produces your final copy.

One strong use is brainstorming, and that can happen at the beginning or at the end of your content process. If you’ve got plenty of grounding material about your business or concept, AI can be very helpful for generating relevant ideas. If you already have a drafted piece, it can be useful for finding weaknesses, holes, or points to expand on.

Another use is summarising and extracting. If you’ve got a large source you want to reference but don’t want to spend ages scanning for key points, AI can help. I would still recommend doing a quick check back to the source if you use AI this way, even if it’s something as simple as using ctrl+f to search the document and confirm that what the output claims is there, is actually there.

AI can also be helpful for generating heading structures. With a thorough brief, models can be good at suggesting a H2 and H3 structure so you can decide what goes where. This way, you keep full control over the content and voice; just make sure to optimise your headings for keywords afterwards so you still properly consider your SEO.

To get the most out of your AI support, be specific with prompts. The more specific the prompt, the more specific the output tends to be. Be sure to also stay within your knowledge base, because AI is not a replacement for your own understanding. If you rely on it to do something beyond what you can personally check, you risk publishing inaccuracies. On that same note, fact-check everything that AI brings up. Do your own additional research, and make sure that what goes live is factual and accurate. 

The takeaway

If there are three summarising points to take away from this, let it be the following:

• Use AI as a support, not a substitute for strategy. Everything that goes into content creation before generating the output still needs to happen, including SEO and research.
  
• Speed has trade-offs, especially for originality in search, so be aware of what you might be trading for efficiency.
• Quality control is what keeps AI content worth reading, because protecting your original voice supports search performance and brand individuality in an online space where everyone is starting to sound the same.

Ultimately, it’s your name and your brand that will be attached to the final, live content, so it’s crucial that the final piece is something that you trust will perform well, and something that you’re proud to be associated with.