Key Takeaways
Uncover the subtle signs of generic AI content that breaks marketing trust, including the use of non-value filler words and formulaic prose. Learn to spot these tell-tale markers such as keyword repetition and inconsistent information to ensure human oversight delivers original, high-quality content that truly connects with your audience.
Assuming you’ve done your due diligence in providing an open AI tool with the right context and your expectations through the prompt, at first glance, the content generated would look impressively flawless. Not to mention, the AI’s confident tone in its response even makes it seem trustworthy. However, if you look closely, you’ll find the breadcrumbs of AI-generated content.
Identifying the Telltale Patterns
Here are some common traits to look for when you receive your next output.
1. Filler words that add little value
Bear in mind that these tools draw from large language models (LLMs), so we’re talking about billions of data points. It’ll naturally infer from the most used buzzwords and stack them together to create the illusion of impactful writing. Humans are more selective with the usage of such words, limiting them to only where there is a need for emphasis, and focusing on the narrative as a lead-up.
2. Keyword repetition
AI often repeats words used to describe or explain your prompt in the output. It’s less obvious in short-form content, but in long-form content, it tends to peep out. Humans, on the other hand, naturally weave in synonyms and related terms to avoid keyword stuffing and keep readers engaged.
3. Inconsistent information
AI can overlook small details that break narrative flow. Imagine requesting a listicle blog in an AI writing tool with four points highlighted, but you subsequently added a fifth. Chances are, it still summarizes only four pointers even when it’s happening in the same chat. AI defers to executing instructions, and unless specified, it’s prone to getting a little short-sighted, working only on the most recent request. Think of it as a junior assistant who only wants to get things done fast, but isn’t detail-oriented.
4. Overuse of question-first headlines
Probably AI picked up on this observation through learning social media samples, where headlining the start of a content with a question drives higher engagement. While it’s still a recommended tactic, would you want your entire company's newsfeed to all adhere to the same question-first format? It’s not a natural style skilled content writers would do for, well, everything.
Why Public AI Tools Can’t Replace Human Oversight
While using a closed, or custom AI solution that is trained in accordance to what you need can help mitigate these situations, the majority of the population does not have that luxury and have to rely on what is publicly accessible. This further drives home the importance of human input in the entire process of AI-generated content.
Take Ownership as you Would, Pre-AI days
Take pride in every piece of work you release, and check the work created by AI thoroughly using your trained skillset as a marketer. It’s not a roll-back to archaic times; it’s proving that humans are still needed for the delivery of original, quality work.
We live in a time where it’s a collaboration between technology and humans, where one covers the blind spots for the other, leveraging each other’s strengths. An AI easily speeds up the production process, but skilled marketers must step in to question, tweak, and strengthen the quality of the asset.
