How To Generate AI Content That Reads Well

The Evolution of AI in Content Creation

Before we look at possible ways to combat readability issues, we first need to understand how it came about and what tell-tale signs to look out for. AI started its journey in content creation with basic tools that helped with spelling and grammar. Nowadays, it includes advanced tools that assist in writing, editing, and even creating whole pieces of content.

How AI is Changing the Way We Process Information

AI’s impact goes beyond just creating content; it also affects how we access and understand information. Technologies like Natural Language Processing bridges human-computer interaction. Discover its key aspects, workings, and applications today!") (NLP) are perfect for making complex texts easier to understand and summarizing information.

By using personalization algorithms, AI customizes reading experiences based on individual preferences, suggesting materials that match a reader’s interests and reading level. This personalization is especially noticeable in e-books and digital libraries, where AI recommends books based on what you’ve read before, enhancing how engaged and knowledgeable a reader becomes. Therefore, AI not only changes how content is created but also what and how is experienced.

However, this reliance on AI in consuming content can backfire when poorly generated content dominates digital spaces. Instead of enhancing the reading experience, it may create barriers—confusing readers with jargon-filled text or overwhelmingly leaving out important information.

How to Spot AI-generated Content

You’ve probably heard “AI” and “vague” used together in a sentence countless times. One of the key issues with past AI-generated content has been people forcing it to write about current affairs. Despite being warned about the models having limited knowledge, the same people would then go on to get mad that AI hallucinated or created extremely vague content. Even worse, they would make the blatant misinformation public without thought, with such a plague even reaching academic journals.

Thankfully, the vague and plainly hallucinated content is a thing of the past. The newest general LLMs have real-time access to the internet, and specialized platforms such as FlowHunt allow you to create dedicated knowledge bases instead of costly model training. But even with fresh data, the AI content readability issue prevails.

The AI content readability issue can also be dubbed the “AI tone”. From overly polished yet soulless phrases to unnecessarily long sentences, it’s easy to tell when something has been written by a machine. The lack of personality, nuance, and bad readability not only frustrates readers but also undermines the credibility of authors and businesses.

Thousands of AI-generated articles flood search engines daily, most designed to game SEO algorithms rather than deliver value. This approach degrades user experience, leaving audiences disconnected from the material. FlowHunt addresses this by prioritizing human oversight and creative input, enabling users to generate content that is rooted in real and fresh data while also fitting in with the author’s or brand’s voice.

Why Quality Control in AI Content Matters

Quality content isn’t just about readability—it’s about trust. Readers can spot the difference between thoughtful, engaging writing and something churned out by an algorithm. Poorly written AI-generated content erodes this trust, making it harder for businesses and creators to stand out. FlowHunt.io tackles this issue by providing tools to refine AI output, ensuring every piece of content aligns with your brand voice, your knowledge base, and the audience’s expectations.

Having Quality control workflows when generating at scale is essential in cutting through the digital noise and delivering real value. AI-generated content quality control is everything from pointing it to the right topic and making sure it has enough context all the way to checking the language, rewriting, or adding new sections.

The first step to fixing the readability of your content is to understand the current level. You can usually get a good idea by simply reading and being mindful of when you’re losing focus and why. But there’s also a way to put a number on readability. There are many scales and frameworks to analyze text and assess readability based on various language and psychology metrics, with Flesch-Kinkaid being the most popular one:

Analyzing text in FlowHunt’s free readability checker tool

Do you want to see how well your AI-generated content reads? Use our FREE readability checker tool.

Overcoming AI Content Readability Challenges

The Decline of Traditional Reading Habits

The way we create, read, and take in information is changing whether we like it or not. In the past, reading was all about really understanding and thinking deeply about what we read. Today, it’s easy to get quick surface-level summaries from vague or hallucinatory content. It’s important to recognize this change and find ways to keep a good balance between the quick help AI offers and the deep creative and reading skills we used to have.

How to Generate Readable Content

Even if it may sound counter-intuitive, AI can help make your content sound less like AI. Always keep in mind that AI simply does what you tell it to. If you don’t specify the way you want it to sound, the information to mention, and the keywords to use, it simply will not do that. By using advanced tools and taking the time to understand AI, content creators can improve how effectively they can generate content.

Prompt is King

One simple strategy for better AI-generated content is setting clear rules. Rather than letting AI dictate tone and structure, you should actively guide the process. When talking to ChatGPT and other models, your best weapon is a cleverly crafted prompt using widely recognized prompting techniques.

Here’s an example of an incomplete prompt that lets AI dedicate the tone and structure:

Write me an article on remote work.

Complete prompt for ChatGPT:

Topic: "The Benefits of Remote Work for Productivity"
Purpose: To create an engaging blog post aimed at mid-level managers, explaining how remote work can boost team productivity while addressing common concerns.
Audience: Business professionals, especially managers of small to medium-sized teams, who are skeptical about remote work's impact on efficiency.
Tone: Professional yet conversational, optimistic but realistic. Avoid excessive jargon; keep it approachable.
Style Guidelines:
- Use short paragraphs and subheadings for readability.
  Include one statistic per section for credibility.
  End with a call-to-action encouraging managers to pilot a remote work policy.
Output Length: 600-800 words.
Structure:
- Body .....
Title: A clear, compelling headline that highlights the benefits.
Introduction: Start with a relatable scenario or question about remote work. Keep it concise but hook the reader.

Imagine writing all that each time you need to generate something new! There’s a much better way to do all this.

Forget having to always prompt general models based on what you need. There are many platforms specializing in giving you power over how your content is generated. Platforms like FlowHunt, Copy.ai or Jasper empower creators to choose a style that reflects their voice, ensuring every piece resonates with readers.

Remember the incomplete prompt? There’s a way to use it and still get the right output. The key is to have a pre-prepared tool template with the complete information already in it. All you have to do then is simply give the topic.

In FlowHunt, your tool might look something like this. Your Prompt on tone, structure, and audience would always be within the tool and ready for you to give it a topic:

An AI-writer agent connected to a writing task in FlowHunt. It knows the tone and structure you need, all you need to add is the topic.

With all the repeatable instructions already in place, all you need to input is the topic and keywords. The Flow will let you know what and why is it doing at any point during generation:

From simple tone settings to training models to use your voice and crafting heavy-duty prompts, there’s many ways you can keep getting closer to content that feels more human and provides real value.

Are you interested in the writing tool above? Try it for free here!

Try Experimenting with Different AI Models

How many times have you seen the “In today’s fast-paced world…” introduction and immediately felt a bit ill? There’s good news. That one is purely the domain of GPT-4o. It’s the most popular AI choice in the world, but maybe it’s not the right one for you. Other leading models are just as apt at writing content as GPT, but each brings something a little different.

If you generally like the way GPT-4o writes but you’d like it to quit using the same phrases, then Meta Llama is the way to go. The readability and structure are very similar. For easily readable no-fluff content, give Anthropic’s Claude 3 a try. Lastly, if it’s the bland tone that makes you mad, check out xAI’s Grok. To find out more about how these models stack up, see our content generation comarison. Or jump right into FlowHunt try out all of these models with a single subscription.

You Still Can’t Afford to Skip Human Oversight

Being specific about the tone you want is the best way to combat the dreaded “AI Tone”. Even with the best prompt in the world, AI is still prone to making mistakes.

By combining AI’s efficiency with human creativity, we can move beyond the lifeless, cookie-cutter content that floods the web. Instead, we can generate material that is clear, thoughtful, and engaging—content that readers trust and enjoy.

Looking Ahead: The Future of AI Content Readability

Predictions for AI and Reading

As we look toward the future, it’s clear that the partnership between AI and human creators will define the digital landscape. The question isn’t how much content AI can produce but how much of it will be worth reading. By focusing on tools that emphasize human input, like FlowHunt.io, we can create a future where AI enhances communication without sacrificing authenticity.

As we look toward the future, it’s clear that AI will greatly impact how we create, read, and interact with content. By 2030, AI is expected to make reading experiences much more personalized. This means that the same content will be presented in such a way to fit each person’s likes and how they learn best.

This personalization won’t just make reading more interesting; it will also help people understand what they’re reading better by showing information that matches how they think. Additionally, AI will change how we find and use information by making it possible to customize reading materials like never before.

The Continuous Evolution of AI Content Readability

The readability of AI content will keep improving as AI technology becomes more of a part of how we create and share content. Partially thanks to the advancements and AI learning to write more like humans do, but also thanks to the sheer amount of generated content slowly shifting our content consumption habits.

This progress will lead to more user-friendly and interactive reading platforms where AI helps break down complicated texts into smaller, easier-to-understand parts. AI’s role in improving readability will also mean better support for different languages, with real-time translation and context-specific changes to help people understand content across various cultures.

In conclusion, the future of readability with AI looks bright and full of possibilities. There will be a continuous effort to better the user