Everything You Need to Know About AI Content
Unless you’ve been hiding under a rock for the past couple of months, you’ve definitely heard of AI content—or, more specifically, ChatGPT.
AI-generated content has been disrupting various industries, from ecommerce and customer service to entertainment and education. With AI neural networks and machine learning models getting increasingly sophisticated, computer algorithms can now generate high-quality content with minimal human intervention.
So, is content production going to be the next big victim of AI content?
Will AI replace human writers altogether?
Or is it a dangerous technology that raises more questions than it answers?
As always, the answer lies somewhere in between. Let’s attempt to decode the capabilities of AI content and what it means for content creators and SaaS marketers.
What Is AI Content?
AI content or AI-generated content refers to any content created by computer algorithms.
These algorithms are trained using machine learning (ML) models to replicate human-generated content. Huge data sets are fed into these ML models to equip them to generate content like articles, blog posts, news reports, social media posts, and more based on user prompts.
While AI-generated content is nothing new, Open AI’s GPT-3 model has renewed larger interest in this space. GPT-3 is the biggest neural network of its kind and has taken huge strides toward completely human-free content creation. Users have been able to extract answers to queries, long-form content based on simple prompts, and even translations, computer code solutions, and medical advice.
With the help of rapidly advancing neural networks like GPT-3, marketers and content creators are feeling increasingly confident to incorporate them into their content generation workflows. But there still exist complex intricacies when it comes to completely trusting AI for your content creation needs.
When Is AI Content Harmful?
The limitations of AI content can be traced to its fundamental nature.
AI is NOT all-knowing
It’s a form of ‘artificial’ intelligence that relies solely on what is fed into it. The output generated by neural networks and AI software in general is only as good as the data set it’s trained on. Any inherent drawbacks with these data sets will directly translate to drawbacks in the AI content.
AI can pump out incorrect content
One major drawback, especially with content creation in mind, is the possibility of inaccurate content. Even the most advanced AI models like GPT-3 are known to often produce output that’s not factual and sometimes, incredulously wrong 😱
AI can make things up (little liar)
AI content can even make up facts and fill in gaps in information when it doesn’t have an answer to a query. This poses serious questions about its reliability and hence, its role in content creation.
AI can be oblivious to offensive content
Another real danger of AI content is that it can unknowingly generate biased and even offensive content. As it can’t detect bias in a piece of content it’s pulling from, it can often churn out content that, if published as-is, poses grave threats to an organization’s reputation.
AI creates same-y content
There is also the issue of homogeneity in AI-generated content.
If everyone starts using AI tools to produce articles and marketing content, there will remain very little differentiation between your and your competitor’s copy.
Google has even gone on record to bucket AI-generated content with spun and automatically generated content. This essentially means Google is likely to penalize sites relying on AI content, hence hurting their SEO ranking.
For content creators and SaaS marketers, relying solely on AI content will do more harm than good. As AI is naturally devoid of nuance and original thought, it can’t truly replicate content that’s well-researched, 100% accurate, and distinctly original.
For example, an AI model cannot interview experts in the field, can’t conduct new research, or provide new insights into a topic.
Any marketer would agree that this doesn’t bode well for content that’s meant to communicate their brand’s unique voice and personality to their customers.
When Is AI Content Useful?
AI content can help writers in an assisting capacity to automate repetitive elements of their workflows so they can spend more time writing unique and persuasive content.
Save time on repetitive tasks: The strength of AI models lies in their ability to save writers hours of time by generating outlines, briefs, and content ideas. They still require human intervention in terms of vetting and fine-tuning the output but it nevertheless helps ease a bit of the burden from writers’ shoulders.
Leverage it on tasks that don’t require much skill: For instance, marketers can leverage AI content for article templates, headlines, short introductions, and more. These applications of AI content can get rid of writer’s block and grease the wheels of creativity when marketers are struggling to articulate an idea.
Automate and scale projects: Large-scale content creation inevitably requires some degree of automation and standardization. Today’s content marketing realities dictate that marketers get theory hands on all possible tools that can help scale content generation. This enables them to stay competitive while also freeing up invaluable bandwidth to create content ideas that truly set them apart.
Content creation is a journey that begins with an idea, builds on top of it to shape it into a story, and embellishes it with original insights and useful sources. The necessity of the human element in this journey isn’t going away anytime soon as AI tools can only do so much when skill-heavy elements of the process are concerned.
How Can SaaS Brands Use AI Content?
SaaS businesses are producing more content than ever, from web copy and product descriptions to social media posts and thought leadership blogs. As the scale of content creation keeps growing in response to business growth, marketers are bound to find themselves short-staffed to keep up with the demand for content.
This is where AI content can step up and share the workload, handling low-effort, repetitive jobs that keep hogging all of your bandwidth. These tasks can include suggestions for titles, headings, and outlines, and can even help churn out topic summaries to inspire marketers with more ideas.
A few specific use cases where AI content can really bolster your content production process are as follows:
1. Keyword Research
Content writers and SaaS marketers are already going beyond ad copy and article outlines and leveraging GPT-3 for areas like keyword research. Sure, you can conduct traditional keyword research using pre-existing tools but using GPT-3 can speed up the process.
You can type in a prompt like “list of keywords for a high-ranking blog post” to obtain a list that’s fairly accurate and agreed upon.
2. Blog Post Titles
Blog titles are a common source of frustration for marketers, considering they need to work on dozens of blogs every month. AI content can help you quickly generate innumerable variations of titles and headings using a simple prompt.
Entering a prompt like “list of titles for a blog post on content creation” will return suggestions like “Maximizing the Impact of Your Content: Strategies for Success” and “Writing with Purpose: Creating Content that Connects with Your Audience”.
3. Content Briefs
Content briefs generated with AI can templatize content production and help marketers focus on the more creative aspects of the process. Based on your existing content, GPT-3 can create briefs for articles and blog posts that can come quite close to human-generated outlines. Granted, these briefs will still need some refining but the bulk of the job will already be done by the AI model.
4. Outlines
You don’t need to limit yourself to generating briefs. You can even create outlines and content strategies using GPT-3. The neural network is sufficiently trained to scan existing content (both yours and the competition’s) to then emulate different writing styles and deliver well-organized outlines.
5. Introductions
Often marketers are plagued by writer’s block when expanding their topics and headlines into complete articles. GPT-3 can help produce introductions and summaries that can spur you into action by providing different routes for your thought process.
As long as you’re writing on topics that aren’t too abstract or radically new, the model can generate accurate and comprehensive intros for your articles.
6. Inspiration
GPT-3 can even act as a source of inspiration when you’re stuck deciding on your next big idea.
With access to a colossal data set and getting refined every day based on users’ interactions with it, GPT-3 can provide you with content ideas ranging from the tried-and-trusted to the fantastical.
For instance, you can simply type in “content ideas for a viral blog post” and you’ll get responses like “An expose on a controversial issue or hidden truth” and “A humorous take on a popular topic”. These responses are meant to trigger an idea already residing in your mind but buried somewhere deep within.
AI Content Can Make Writers Better, Not Replace Them
AI content has the potential to revolutionize the way we produce, access, and consume information. SaaS marketers stand to gain a lot by adding it to their existing tech stack to assist writers and not replace them. It’s important to remember that while AI is highly capable of generating high-quality content if used correctly, it cannot replace the unique qualities that humans bring to the table, such as creativity, original thinking, and empathy.
Want a juicy content tip delivered to your inbox every Wednesday? Sign up for the Content Writing Chronicles ASAP—you will not regret it!
