In just a few years, we’ve witnessed artificial intelligence (AI) tools evolve from fun toys that can generate low-quality but creative pictures to a global trend. Now, every company, from small agencies to Meta, is trying to implement an AI tool, and many content creators are figuring out how to use generative AI in content creation and other creative industries.
The trend is unlikely to stop, as the market for AI solutions has doubled since 2020 and is projected to quadruple by 2030.
But such a rapid AI revolution leads people to a common misconception — they believe AI is a magic wand that can do anything with little input. Sadly, that’s not the case.
Generative AI (genAI) is a tool, and using it requires understanding its limitations and capabilities. If you’d like to use generative AI in content creation, this article will walk you through all the details.
Generative AI and Its Core Models
GenAI is a very broad term. In any AI tool, multiple mechanisms might work under the hood.
The two most prominent GenAI models are Natural Language Processing (NLP) and Artificial Neural Networks (ANN).
The NLP model is used to help the application process human-written text. This technology works with large quantities of text to summarize and analyze it and converse with humans like ChatGPT does.
Neural networks mimic how the human brain works by using multiple nodes connected like neurons. These networks use linear algebra principles to form connections and are used to find patterns in data or images. ANNs are particularly useful in image recognition.
ChatGPT, one of the most widely recognized AI models, operates as a type of Natural Language Processing (NLP) model called a Large Language Model (LLM). Its main role is to interpret user questions posed in natural language and generate conversational, contextually appropriate responses.
Many AI tools on the market today utilize frameworks that leverage ChatGPT or similar LLMs, essentially structuring which model should answer particular questions while incorporating additional prompts to refine and enhance response accuracy and relevance.
Advantages of Gen AI for Content Creation
83% of content marketers use some form of AI to assist in writing. Here are three reasons you might want to do that too:
Produce Content Faster
The quality of generative AI in content creation is still lower than human-written content, but it excels when it comes to speed.
With an AI tool, you don’t have to compromise on the quality of the content, though. Instead of generating the whole text with the help of AI, you can:
- Find content ideas
- Create an outline
- Create a first draft that you can edit
- Create iterations on specific paragraphs
- Proofread for tone inconsistency
- Add keywords to the text
- Create routine texts like product descriptions
Another area of content creation where AI tools shine is content repurposing. Generative AI might sound repetitive in a longer text, but it summarizes content well. So, if you use long blog posts to break down into shorter social media posts, AI is a great tool.
You can also use AI to create illustrations for your content. Especially considering the fact that many free stock images have already been created by AIs. For data visualization, using more advanced tools like ChatGPT Plus with Code Interpreter is better.
Adaptability
AI tools can churn out content at an astonishing pace. If you need to create hundreds of product descriptions or meta titles for a new site or a new batch of products at your store, AI can do that in a single day.
Whether creating content for customer education or as sales collateral, AI can quickly adapt to the style, audience, and tone of voice you need to use.
The same goes for speeding up the content creation process for a new event you want to capitalize on.
AI tools can also adapt to most languages. This means you can go to worldwide markets with little to no effort.
Budget-Friendliness
AI tools can do all of the above and more incredibly cost-effective. The basic ChatGPT functions are available for free. Using its API and more advanced models costs around a couple of dollars for a million tokens.
Tokens are units of text (parts of words) used by the model to process language, with each word generally split into one or more tokens. For context, a million tokens is roughly equivalent to 750,000 words.
The cost reflects the computational resources needed to generate responses using advanced AI models.
So, if a developer uses these models for applications, they are billed based on the token usage rather than flat-rate or per-request fees, making this pricing approach efficient for scaling responses in larger applications.
Most generative AI tools will set you back around $30-$50 per month.
Advanced Content Marketing with Generative AI Usage
Creating content is a big part of SEO, as most of the traffic you can direct to your site is informational. As AI tools become more and more proficient at creating content and providing information, new AI content marketing strategies are emerging.
Let’s take a look at three things you can do with AI that would take a ton of time and effort otherwise.
Personalization
The first and probably the largest benefit of using AI in your content strategies is the vast options for personalization it provides.
A bit more advanced personalization would require you to integrate AI tools with your website and content management system. This way, you can dynamically provide personalized content to users as they browse the website.
For instance, you can address the user by their name on the website or offer content suggestions based on previous experiences.
An easier level of personalization is using AI to tailor your content to the ideal customer profile (ICP) you have in mind.
AI tools are known for impersonating people and copying writing styles. You can feed a conversational AI model the basics of your ICP and ask it to use that model to come up with topics the ideal customer would like.
Once it has learned what your ICP is, you can use it to create or check existing content ideas to ensure they’re personalized for your audience.
When you’re done with creating text, you can put it into the AI tool and ask it to check whether it’s written in a way that would resonate with your specific audience and show what can be improved.
Creativity Boost
Generative AI models are also prolific at coming up with ideas from different angles. Sometimes, when you can’t come up with anything, AI is just what you need to get started.
Granted, some ideas won’t be usable either because they’re too generic or just don’t fit. But that’s fine as long as you get a lot of ideas.
However, you can generate much better ideas if you use specific prompts. Instead of simply telling the AI to generate article ideas or outlines, tell it to use your ICP and your brand voice to make the answers better tailored to your specific needs.
This will result in more ideas that your ideal audience would be interested in instead of something generic.
SEO Assistance
AI tools can be of great use in SEO as well. But you have to know what you’re doing to get it right. Asking ChatGPT for relevant keywords is probably not going to work.
What you can do instead is use an SEO tool with AI capabilities. Tools like these can analyze articles in your target keyword SERP and suggest how to optimize them better.
The list of suggestions often includes keywords and their count in content, topics you should cover, the article's word count, and more.
At this stage, you would have a detailed document describing how to optimize your content. You can then ask a generative AI tool to generate an outline based on this document.
Once you have a draft, you can use generative AI to rewrite some paragraphs of the text to add keywords you’ve missed or other optimization elements.
GenAI Limits & Challenges
GenAI in content creation is a tool. An unprecedented one, but a limited one as well. One of the biggest limits of current GenAI models is the risk of providing wrong data.
GenAI can’t use reasoning and logic. And it can’t verify information.
On top of that, it can sometimes hallucinate and make up information.
So, any statement or data point provided by the AI should be fact-checked for accuracy. In many cases, it will provide accurate data with a citation, but the only way to know if that data is true is to follow that citation and check it yourself.
An extension of that is limited access to current events and data. Most AI models are trained on a set of historical data and don’t have access to the internet or the ability to train in real time. So they just don’t have the knowledge of recent events.
Another limitation is that GenAI cannot make predictions, because it doesn’t use logic. Other AI models can do that, but those should be trained specifically to recognize patterns in data, and GenAI can’t do that.
The biggest challenge of GenAI in content creation is that it sometimes can take a bit of time to create the right prompt to have the answer you’re looking for. You can avoid that by using a prompt template or experimenting until you find one that works for you.
Examples of AI Content Usage
Thousands of companies are likely using AI to assist with creating content in one way or another. But it’s impossible to assess how exactly they’re doing this without talking directly to the people involved.
Instead, we can look at how companies use AI-generated content. There are quite a few examples.
Bankrate and CNET
Bankrate is a quite popular informational website. CNET is a news media publication.
Both Bankrate and CNET started using an AI-based content strategy and published a series of articles with a disclaimer that they were created using ChatGPT and edited for accuracy and clarity by an expert. While many articles enjoyed a brief period of high ranking on Google, eventually, both sites reduced the number of AI-generated articles.
The main reason behind this is likely the number of inaccuracies that made it to the final versions of the articles. Google has recently updated its helpful content guidelines to combat poor-quality content, and inaccurate data might have hurt rankings.
LinkedIn had a much better idea for using AI-generated content. The website already has a blogging platform, LinkedIn Pulse. Since it’s a social media platform, first and foremost, it has a large potential for creating content together.
That’s exactly the idea behind LinkedIn collaborative articles. The AI creates an article on a topic, and experts can provide comments and perspectives.
Judging from the fact that collaborative articles still exist and are quite popular on the platform, this way of using AI to provide general information and start a conversation works better than simply using it to write an article.
Using a Learning Platform for Content Creation with GenAI
Brooks Automation, a leading automation provider and trusted partner to the global manufacturing industry, recently trusted a learning platform powered by AI for its training content and e-learning needs.
They wanted a platform that could deliver personalized learning experiences, automate administrative tasks, offer extensive customization, and support scalable growth as the company expanded.
Leveraging a learning management system (LMS) or learning platform can supercharge content creation, especially when integrated with GenAI tools.
Whether it is for training and development, customer or partner education, or even sales enablement, an LMS enables companies to create, track, and personalize learning content efficiently.
Paired with GenAI, LMSs can automate content updates, streamline customization for specific audiences, and improve engagement metrics, making them invaluable for companies offering training content or any kind of e-learning.
Did you know that it takes around 40 hours of work to produce just one hour of training material? With GenAI, new content generation takes minutes.
Whether developing internal or external resources or courses for e-commerce, an LMS GenAI authoring tool that is pedagogically sound ensures a fast and efficient way of producing accurate content for your different audiences.
Brooks automation leveraged their learning platform with AI authoring tools for e-commerce, and unlocked a new revenue stream from their training programs by offering e-learning and instructor-led training as paid services.
How to Use Gen AI to Produce a Quality Post?
There are six major steps you need to go through to create a good piece of content. Here’s how to use GenAI in content creation in five of them. With the sixth step, you’ll have to put in more work yourself.
Finding Topic Ideas
The hardest part is always looking for a great topic to cover. Use AI for brainstorming to get more ideas. With a bit more sophisticated approach, you can come up with topics that aren’t generic.
Give your AI tool a description of your ideal reader or a keyword to focus on. This way, you’ll get topics more specific to your blog and your audience.
Source: ChatGPT
Play around with the AI tool until you find a couple of topics that seem decent and alter them to fit your blog.
Researching the Topic
The next step is researching the topics you’ve chosen. Start with keyword research to understand what articles rank for the keywords associated with them and gauge whether your article can rank high on Google. You can do this with AI tools that specialize in SEO.
With regular generative AI models, you can research the general points you can cover in the article and statistics you can add to support your arguments.
Ensure to check the statistics for accuracy before using them.
Source: ChatGPT
Making a Detailed Outline
Based on the research into the topic, AI tools can generate an outline for your article.
Source: ChatGPT
Don’t use the outline as is, though. AI tools can generate a pretty basic outline but can’t create anything new. Your role here is to add expertise and nuance to the outline to ensure it can answer the user's search intent.
Creating an Optimized Post
At this point, you can use the outline that you’ve created to write an article. You can also use GenAI tools to create a first draft.
If you’re going to use this text, keep in mind that it takes heavy editing to make it look high-quality.
Source: ChatGPT
Iterating Content
Writing the whole article with an AI tool might be a hard task as it takes a lot of editing and revisions to look like it was written by a human. What you can use AI for instead is doing iterations on content.
AI can rewrite any part of the text to see how it would look with different approaches to style and tone of voice, or how it would look for a different target audience. You can also try using AI to add keywords to the text.
If you’re using AI to make iterations on your text, proofread it well after this.
Source: ChatGPT
Editing, Fact-Checking, and Proofreading
The final part of creating any type of content is the editing process. AI can’t help you with that. Here are the areas you have to focus on when proofreading content made with AI.
- Accuracy of statistics used in the text
- Accuracy of general statements used in the text
- The flow of the text and breaks in logic
- Unnecessary repetitions
- Phrases that break the style and tone of voice
After this, look for opportunities to improve the AI-generated text by adding more context and expert opinions on the topic.
Summary
Using GenAI in content creation can speed up the process quite a lot, but it isn’t without some limitations.
Focus on finding ways to use AI to increase your creativity and productivity, but always rely on your own judgement when it comes to fact-checking and editing texts produced with the help of AI.
This way, you can take the best parts of GenAI and avoid its drawbacks.
To ensure accuracy in content creation, Docebo uses a pedagogical research-backed AI authoring tool.
Book a demo to know more about the learning platform trusted by 3,800 businesses worldwide.