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With the range of technology that marketers can use for both content marketing and generating new content ideas, it’s no surprise that content generation itself can and would benefit from the use of Artificial Intelligence (AI). 

At okwrite, we engage the support of an AI-powered brand to guide our content creation. But there are additional technologies that use AI to actually write the content. 

This kind of technology for content marketers is still in its infancy and it has been interesting as a company to witness its evolutions. Considering the importance of creating original content, we thought it would be best to create a piece that takes a dive into content generation and AI. We will explore the ways in which the content generation process is supported by AI and the ways in which the entire process is completed by Ai. 

If you are interested in this emerging technology like us, you’ve come to the right spot. 

What is Artificial Intelligence?

While it might sound like something out of Ex-Machina, Artificial Intelligence is here and is used every day by millions everywhere. Early work around AI technology began in the 1950s, 60s, and 70s developing neural networks. 

By the 1980s and growing into the 2010s, researchers and those in the computing industry focused on machine learning and natural language. And now, with the help of natural language processing, researchers have moved into deep learning. 

While the function of AI and machine learning are usually interchangeable, it’s important to note that this is not the case. Machine learning is a proponent of AI, but they are not the same thing and there are big differences between the two. 

A simple way to think about it, which was articulated by SAS, is this: 

  • AI is the science of training machines to perform human tasks. 
  • Machine learning is a subset of AI that trains a machine on how to learn. 

In general, the usefulness of training machines to eventually perform AI-type tasks is all part of the process of AI evolution and development. AI is a way of adding “intelligence” to a machine through deep and repetitive task learning. It is also an accurate method of doing this since mechanical neural networks are integrated into the AI network. 

And of course, in order for the AI to be AI, they cannot be programmed by humans; instead, they must progress on their own, typically through a progressive algorithm. 

The Role of AI in Content Marketing

Like numerous apps, software, and technologies, digital marketing has also found ways to use this powerful technology to improve content marketing from its production to its promotion. 

AI marketing is used commonly in news feeds and social media, as well as in improving customer experiences (by means of the chatbot) at certain points of the buyer journey. What intrigues us the most is automated content or the potential for personalized content to be used by an AI writer.

There are a few ‘models’ of AI that can actually spit out some decent looking content. Programs like GPT-2, GROVER, MarketMuse First Draft, and XLNET have been known to produce content from AI alone. 

While many news publications touted that content writers, especially popular media writers, would soon be out a job, many people don’t believe that writers will be outperformed or out-dated thanks to AI anytime soon. 

One company that emerged as a leader of this technology early on is Narrative Science. In 2011, Narrative Science responded to a call from Dead Spin writers who claimed that a story written by George Washington University had instead been written by an AI. They felt this way because the story, about a baseball game, had not mentioned the pitcher, who threw a perfect game, until the 7th paragraph of an 8th paragraph story.  

Narrative Science input the game’s box score into the content generator, and here is an unedited snippet of what was produced written in a “neutral” POV:

Tuesday was a great day for W. Roberts, as the junior pitcher threw a perfect game to carry Virginia to a 2-0 victory over George Washington at Davenport Field.

Twenty-seven Colonials came to the plate and the Virginia pitcher vanquished them all, pitching a perfect game. He struck out 10 batters while recording his momentous feat. Roberts got Ryan Thomas to ground out for the final out of the game.

Tom Gately came up short on the rubber for the Colonials, recording a loss. He went three innings, walked two, struck out one, and allowed two runs.

The Cavaliers went up for good in the fourth, scoring two runs on a fielder’s choice and a balk.

Turns out the robotic content generator can handle itself. Needless to say, we’re impressed, but this does not mean that we’re turning to AI for content writing any time soon.

Outside of the production of the content itself, AI technology is also used to better understand marketing trends and can be a useful AI tool for content recommendations. 

Predictive intelligence allows content creators to understand where their buyers are at during the buying process. Predictive intelligence might focus on which marketing campaigns to prioritize, keywords to target, or identifying where along the buyer journey a prospect is.

With predictive intelligence, marketers can more accurately determine lead prospects and yield significant ROI for even those companies with overall lower lead volumes.  

Most commonly, content marketers look to predictive intelligence to understand the nuances of a given piece within a broader marketing context. This might mean using the AI system for content curation, to identify marketing paths for content production, in deciding which content to promote and when, and determining the type of content to promote at a given time, especially for goals in lead generation

Should You Use a Human Writer or an AI Writer? 

While us content writers might cringe at this question, it is a fair question to ask and one that might start popping up with greater frequency. 

Thanks to the development of these tools as well as their public platform for development, an AI writer is an entirely feasible consideration for a small business. Just look at AI Writer, which promises to deliver custom AI content within a minute based only on a headline. However, even the AI agrees that content generation shouldn’t be relying solely on an AI writer. 

The bottom line is that AI writers are capable of producing somewhat unique content. This unique content might not be read, and the critical eye will easily be able to distinguish when content is written by a human or an AI (or a very bored human). 

Therefore, if you are just seeking to churn out content and you do not care whatsoever about what the content is or the tone of the piece, then the AI writer might be your best fit. 

With updates to Google’s BERT, though, we will strongly caution against this. Google’s BERT is a way of saying that the Google searches are powered by a natural language processor (NLP) machine. 

While previously, searchers would be forced to plug in fragmented words to form a “keyword” search, Google’s BERT wants to move away from that. This AI will be able to read into the context of a keywords search and better understand what the searcher is looking for. 

The biggest change that comes from BERT is the ability to discern good, high-quality content from the garbage content. While I have yet to find out whether BERT can discern good, high-quality content from AI created content, the emotive feel and tone of the piece will play a role in the ranking of that page. 

How okwrite Uses AI When Creating Our Original Content

There are numerous useful ways that AI can fit into a content strategy. It can boost lead acquisition, prospect engagement, and marketing direction. Through our own market research and experience, we’ve developed a process that allows for the automating of certain menial tasks as well as organizing our client experiences. 

While it is enticing to consider what an AI can do for content generation, it just does not make sense for producing a high-quality blog or copy content. It may seem obvious to us, but the use of an AI to produce words is functional, at best, but lacking an emotive feel. 

And most of the time we are not interested in producing articles that are focused on delivering the stats of a baseball game. Our words are evocative, true, and create a personalized experience for the reader; this is not something that we would feel comfortable leaving in the hands of a robot. 

When it comes to content generation, we do use AI for predictive intelligence. Our partner platform MarketMuse, which provides data-driven insight on keywords, page performance, among others, does a bit of this for us. 

Sometimes we can notice the difference in the articles. For the most part, this AI-supported software does not change the quality of the written content; instead, it provides a clear direction for the article. MarketMuse’s AI is designed to guide writers by soliciting the information that the target audience is looking for. 

At its basic level, this type of AI support is pragmatic—it clears out a lot of the information and jargon that is available on the topic and forces articles to be presented more clearly. 

Content Generation Using AI

Content automation and content creation are fueled by AI and can be a powerful arsenal for content automation tools. AI content should in no way replace original content or a content writer, but they can direct a blog post direction, content marketing strategy, and the initial content research. 

Using AI for content generation is necessary so that content marketers can distinguish the avenues, buyer journeys, and interests of target audiences. So, AI for this type of content generation makes good sense. 


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