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How AI is changing the content creation landscape

ChatGPT, Bard, and generative AI at large are being discussed in every major publication now, and frequently pop up in social media feeds — from the excitement of how a product like ChatGPT can write long-form copy to articles about incorrect facts in the new ChatGPT-powered Bing.

If you haven’t started looking at the AI yet, and still not sure if it’s relevant to your work, now might be a good time to start. Unlike any technology we have all seen before, AI is being adopted fast and brings efficiencies that have not been possible until now.

From personalized marketing texts to doing tasks like summarization, generative artificial intelligence is turning the content-creation landscape upside down right before our own eyes — and it’s only just the beginning. AI is changing the way content is created, consumed, and monetized.

How does AI know what content to create?

To understand what AI is capable of, it’s important to understand how it works. We’ll try to keep it simple.

The foundation of generative AI platforms is an LLM, a large language model like GPT-3. 

GPT-3 (Generative Pre-trained Transformer) was trained on 175 billion parameters, and has expertise on an array of topics no human could ever remember. It knows literature, linguistics, logic, chemistry, physics, and has pretty much most of the world’s knowledge at an unimaginable scale. 

Some key concepts to remember:

  • The knowledge in the model is finite
  • It is not updated in real time. 
  • Large Language Model is not search (more on search below). 
  • GPT-3.5 was trained on data through the end of 2021.

Here is what it was trained on:

GPT training data

LLM works by predicting the next word, based on the data it was trained on.

What happens if your brand’s data is not in the 175-billion parameters dataset?

When the original dataset does not include some information that the AI can use to create content, the end result will be a made-up answer. Why? AI will still be predicting the next word when it generates text, and will “do its best” to predict based on the data it has.

You may have seen some criticism of ChatGPT returning incorrect information, and that Google lost $100 billion in capitalization in just one day because Google’s Bard provided a wrong answer in their demo ad.

The answer is wrong because there was no correct information in the initial dataset, and the chatbots provided the answer that was a prediction of the next word based on what the model “knew”. 

Does it mean AI cannot be used because it cannot be trusted?

AI can be used and should be used! It is how you make the most of its use and how you integrate it into the workflow. At Intentful, we have 3 tiers of quality assurance (QA) before the work gets to a project manager (4th tier) and a client (one more check). And it’s not all manual – AI can also check itself by using a different approach; but human involvement, with subject matter expertise, is absolutely essential for any AI-assisted work.

In content creation, AI equals efficiency and optimization

Once you get the process right, you’ll cut the time (and costs!) at least in half. Here is some information about the efficiencies we have seen since the summer of 2021 when we started using AI for content creation:

Accuracy, fact-checking, and search

Both Bing and Google will continue evolving. Both will find a way to connect the chat function to their giant search engine databases, making it available in real time.

If you would like to make sure that customers can discover your product or brand when doing their search on Google or Bing, you need to make sure that:

  • Your content is relevant to search user queries and intent
  • That it follows all of the search engines recommendations
  • When possible, make your content long-form – that gives more information for the robot to analyze.

In terms of accuracy, if we may give a prediction of sorts, there is a very good chance that all future content will have to be marked as created with the help of AI, but will need to also include a reference of who checked it. This is actually in line with the concept of Google’s E-E-A-T.

AI in content creation – use cases

There are hundreds of use cases. AI can augment the creation of multiple types of content:

  • Product descriptions
  • FAQs
  • Targeted emails
  • Personalized ads
  • Segmented lists
  • Blog posts
  • Press releases
  • White papers
  • E-books, and more

You can also use artificial intelligence to revise existing material, adapt it for different channels or regions, or refresh it to keep relevant. Or maybe you need to create product descriptions from SKU specs or descriptions for A/B testing, a content plan for a month, and so much more.

You can expand descriptions of existing content, or ask AI to create a version for another channel. 

Intentful will run a webinar on AI Use Cases in Marketing on March 20th, 2023. Please sign up.

Training the AI model to know your brand

AI was trained on billions of parameters, but it does not know your brand’s voice or facts. It doesn’t know what ads performed best, and what content resonated the most in your blog. But you can teach AI to know all that, and it can become your “super employee” that knows everything and can create content in a matter of seconds. It is important to emphasize that it cannot replace your core staff who defines the content strategy and makes sure what content can or cannot be used. Rather, AI greatly increases the productivity of your content team.

Intentful trains the AI to know our clients’ business. To illustrate what’s possible, here is an example of the AI content that we worked on with the University of Oxford, Saïd Business School. AI was used to impersonate William Shakespeare, Jane Austen, Oscar Wilde and Winston Churchill as part of the Oxford Union debate. The motion of the debate was “This house believes the future of content is AI-based”. 

Nay, nay, I say! This cannot be,

That machines should e'er surpass our art.

We are the masters, them the slaves,

And thus it ever shall be so!

They learn, ‘tis true, but they learn

Only what we bid them learn, no more.

They cannot understand the heart

Or beauty of our words, you see.

So let us not give in to these

Machines - they’ll never be as good

As we are at creating art.

Read more about the project here

The future of content creation work

The rapid pace of change in the media, marketing, advertising, and tech ecosystems often leads to a disconnect between creative agency departments, resulting in a lack of knowledge transfer. Organic content creation remains mostly subjective, and data is not being used to inform the creative process. Paid advertising content remains the priority for most brands. Yet, most brand discovery happens through organic channels.

It will take time before this change starts getting integrated into businesses and workflows, but we know AI is not just about content creation. Because it is possible to train AI pretty much on anything – brand's style, historical communication, best-performing content, new SEO rules, and more – this innovation can free up people to focus on what they do best — be creative and deliver meaningful experiences for customers.  

How to get started with integrating AI

It is easy to get overwhelmed with all the information on the internet. 

There is plenty of information on the internet, but if you would like a more thorough approach, we recommend a book by Dr. Alex Connock, Media Management and Artificial Intelligence.

Media Management and Artificial Intelligence

Schedule a conversation with Intentful to discuss how we can help your company integrate AI into your content creation process, saving thousands of hours and millions of dollars.