Should Content Marketers Fear Artificial Intelligence?

If you’re Bethany Johnson (@thanybethanybe), you learn as much about it as possible.

Johnson is a content marketer who wrote an article for Skyword’s Content Standard about natural language generation (NLG), an AI technology that automatically writes data-driven narratives. She caused a stir among freelancers and writers who feared bots were going to replace them.

“This particular form of artificial intelligence may one day have the potential to put many of my buddies out of a job,” she writes. “What I consider exciting really upset many community members, so I decided to dig into the topic to clarify.”

In Why Natural Language Generation Doesn’t Scare Me (Much), Johnson delivers a fantastic breakdown of what natural language generation is, why NLG matters, and how this artificial intelligence technology will impact content marketers. In the process, she cuts through the hype surrounding AI and assesses realistically what the technology can and can’t currently do.

Should Content Marketers Fear Artificial Intelligence?

One big takeaway is that NLG isn’t here to take your job. In the article, Johnson interviews Paul Roetzer, founder of the Marketing AI Institute, on the topic.

“Natural language generation (NLG) has very narrow applications in marketing today, and, in most cases, it’s enhancing what marketers are able to do, not replacing them,” says Roetzer. “One primary use case is turning data (like structured spreadsheets with rows and columns of neatly organized data) into narratives.”

Using an NLG tool like Narrative Science, marketers can generate an article that describes the data in a spreadsheet. But this doesn’t mean brands will show content creators the door. A human must create the NLG template manually. This requires deep analytical skill and a professional understanding of content marketing. Once the template is created, NLG software can generate stories based on that template—and that template alone.

And the output, while valuable, resembles a “‘death by PowerPoint’ presentation arrangement,” writes Johnson. “They didn’t uncover any trends or relationships. They didn’t draw actionable conclusions. And they’ll never be able to build a case or tell a true story.”

What that means is that artificial intelligence technology like NLG has the potential to enhance, not replace, what content marketers do on a daily basis. In the case of NLG, the tool automates the drudgery of converting data into text, freeing up writers to craft creative, compelling stories around that data narrative.

“I would look at it more as an opportunity,” notes Roetzer in the article. “There’s an emerging market for writers who can take data, envision the narratives that can be told with it at scale, and then construct and improve NLG templates to produce content.”

How Should Content Marketers Adapt in the Age of AI?

Johnson’s article makes it clear that content marketers need not worry about AI taking their jobs. But it also highlights the need for content marketers to evolve in the era of artificial intelligence.

In our work at the Marketing AI Institute, where we connect marketers with actionable information on AI, we’ve identified a few ways content marketers can survive and thrive in the age of artificial intelligence.

1. Have a framework for testing and implementing AI. 

It’s critical that content marketers visualize and organize the marketing AI technology landscape. Tons of AI tools and technologies exist at varying levels of maturity. There’s no single system that incorporates all the potential uses for marketing AI, so marketers must integrate different tools to achieve their goals.

When trying to understand the marketing AI landscape, we couldn’t find a viable framework that served our needs, so we created one. Called the 5Ps of Marketing AI, the framework details how to think about AI across five core marketing areas: Planning, Production, Personalization, Promotion, and Performance. Using the framework, you can identify gaps and opportunities to implement marketing AI. Learn more here.

2. Understand what data you have access to.

Content marketers can create immense value for their organizations by using NLG to create data-driven narratives at scale. For NLG to be a fit, you’ll need to have some type of structured data—data commonly arranged in columns and rows, like in a spreadsheet. It will need to be consistently labeled and arranged, or cleaned up to be so.

More importantly, it should be able to tell a story. Look to the existing stories you already tell. What stories are you already manually telling with your numbers? What stories would be profitable for you to tell if you had unlimited time or budget? Many different datasets have stories to tell, and many can be automated. But currently it takes human insight to determine which stories will be the most useful.

Additionally, any time you communicate the findings of an internal report or dataset, you’re also telling a story. You may be able to profitably automate internal reporting of this kind.

3. Test artificial intelligence tools.

It’s becoming easier than ever to test AI tools yourself. Some marketing automation platforms, like HubSpot, have AI capabilities baked right into their product, so you can get started immediately.

Other standalone products offer free trials that are relatively easy to use, even for marketers with non-technical backgrounds. Tools currently exist that optimize, scale, and improve content using AI. You can see a list of some of our favorites in this article.

For more quality insight into how content marketers must evolve in the age of AI, read Bethany Johnson’s full article. While you’re at it, subscribe to the Marketing AI Institute to receive weekly actionable advice on how to use marketing AI.

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