AI in Content Marketing: What It Is, How to Use It and Companies to Demo

This post originally appeared on the Marketing Artificial Intelligence Institute's blog. The Marketing AI Institute was created and is powered by PR 20/20. 

No matter what content you write or what stories your brand tells, there’s a good chance a machine can help you do it better.

Artificial intelligence, despite any hype or buzz you hear, is a very real force in the marketing industry—and it’s changing the way brands and people create content.

In fact, we surveyed 200+ marketers using our AI Score for Marketers assessment tool, about how valuable it would be to use AI technology to intelligently automate more than 60 common AI use cases in marketing.

Content marketing activities dominated the list of highest-rated use cases for AI in marketing.

Out of the top 10 use cases identified by marketers, seven of them explicitly deal with content marketing functions. These include content analysis, keyword selection, data-driven content creation, optimization, creating personalized content, and A/B testing to improve content.

This majority of respondents were decision makers, with 75.8% identified as Manager (30%), VP/Director (19.5%) or C-Level/SVP (26.3%) titles.

And the use cases they cited are all possible today using AI tools on the market. Tools, we might add, that are becoming more capable by the day.

In short, the marketing leaders we surveyed are hungry for ways to do content marketing at scale. And the technology increasingly exists to do so.

This is an enormous opportunity for forward-thinking marketers, content marketers, and executives who rely on content to drive their businesses. AI can be your competitive advantage, giving content marketers the ability to brainstorm, create, promote, and optimize like never before.

But there is also significant danger that those who fail to understand and adapt to these new technologies in time will get left behind.

In this article, we’ll walk through a working definition of AI for content marketers.

Then, we’ll look at some of the top AI use cases for content marketers, so you have a better idea of how the technology can actually benefit your work—and why failure to adopt it may constitute a serious competitive threat.

Finally, we’ll overview some top companies that use AI to accelerate content marketing performance, so you can start testing tools out on your own.

What Is AI for Content Marketing?

Artificial intelligence is a term that covers a lot of different technologies. You may have heard of some of them: machine learning, computer vision, natural language processing, and natural language generation to name a few.

These technologies use similar principles to perform different types of cognitive tasks as well or better than humans.

For instance, Gmail now uses AI to predict the next word you’ll type in your emails and offer an automatic suggestion so you can speed up your typing. A software assistant like Grammarly uses AI to offer recommendations on how to write better. And your iPhone predicts what might be the most appropriate responses for the text message you just got, so you don’t have to think about what to write next.

In all cases, AI is used, in various contexts, to “read” and “write” human language.

The ability to “read” human language is the domain of an AI-powered technology called natural language processing (NLP). The ability to “write” and “speak” (like Siri and Alexa) is thanks to AI called natural language generation (NLG).

Even the most basic of NLP and NLG systems can analyze and produce human language to some degree.

That’s impressive.

But the real magic happens when these systems are able to improve themselves over time.

A system like Gmail’s Smart Compose offers suggestions on what you should say next, then learns from what suggestion you pick. If you consistently ignore one of its recommendations, chances are it’ll offer different ones in the future.

The most advanced machines teach themselves to improve based on user inputs, rather than relying on a human programmer to constantly update the rules that dictate their outputs.

Now imagine how this plays out in the world of content marketing.

An advanced intelligent machine system reads and/or writes human language. Every time it reads or every time it writes, it learns a little more about how to improve—then it adjusts accordingly.

It may not be perfect. But it gets better fast. We see this play out in other realms of AI, where AI systems have beat human champions at highly complex games like Go. The systems learned faster and at scale.

Suddenly, you’re looking at tools that may be able to read, analyze, suggest, and/or write content far better than humans. Or learn to in a very short amount of time after you implement them.

In early 2019, OpenAI, a non-profit AI research company backed by the likes of Elon Musk, Peter Thiel, and Reid Hoffman, announced they built an AI model that essentially writes coherent paragraphs of text at scale.

The model is called GPT-2 and it learned how to write this well by analyzing eight million web pages.

The point here isn’t to say AI will replace writers or remove the need for content marketers.

It’s to highlight that this is real technology that is making real progress towards doing certain marketing tasks better than humans.

In fact, most marketers would be shocked to learn AI technology that exists today can perform certain content marketing tasks—like writing email subject lines, identifying gaps in content strategy, and suggesting keywords—better than humans.

Yet it’s true.

Read on to learn just a few of the things AI in content marketing can do.

Check out the Artificial Intelligence for Content Marketing and Email 101 Workshop at the Marketing AI Conference (MAICON), July 16, 2019 in Cleveland, OH.

Use Cases for AI in Content Marketing

Content Production at Scale

Short-form content creation is already possible. Commercial AI systems exist that can draft email subject lines and certain types of ad copy. These systems are used to generate text automatically, without human involvement, that converts at higher rates than work produced by human copywriters.

And thanks to OpenAI’s GPT-2 model mentioned above, longer-form content creation may become possible with advanced AI.

It’s too early to tell how this type of advanced AI will be operationalized in marketing, but the implications are too large for content marketers to ignore. We could be looking at an AI-powered future where humans and machines work hand-in-hand to actually write marketing content. It’s already happening in short-form email subject lines and ad copy. It’s possible that blogging or more involved content creation is next.

Content Strategy and Intelligence

Many content marketers rely on gut instinct to build content strategy. When we do rely on data, there’s often too much of it to effectively sort the signal from the noise.

Luckily, AI exists that does a better job than people of providing data-driven insights to inform content strategy.

Systems exist that analyze your content performance data, compare that data with other sites, and offer predictions about everything from what to write to what topics perform best.

These systems go by many names, like content strategy platforms or content intelligence tools, but they use AI to achieve the same goal: Provide insights that leads to smarter content strategies.

Content and Search Optimization

AI can help optimize content before and after it’s published, reducing the manual work required to get the most out of content investments. AI systems can handle key optimization tasks like:

• Content research
• Topic suggestion
• Brand compliance across assets
• Search engine optimization
• Content alignment with user intent

It’s true: With AI systems that exist today, you can automate a significant portion of the heavy lifting required to optimize each and every piece of content.

Content Personalization and Recommendation

AI was designed to make recommendations, using data to predict what you’ll like. You see this in the AI systems used by Netflix and Amazon to suggest offerings. And the same principles are used to power AI content recommendation.

There are AI tools that will analyze the content consumption habits of site visitors, then recommend pieces of content they might like to consume next. The very best of these systems learn dynamically based on user actions, getting better and better at predicting what you might want to read, watch, or listen to next.

AI Companies with Content Marketing Application

The first step in evolving your content marketing with AI is understanding the use cases. Next is exploring AI companies that offer a solution for your needs. But, it's a larger undertaking than you may anticipate— in fact, we’re tracking more than 1,110 sales and marketing AI companies with combined funding north of $5 billion, and plenty of them have content marketing use cases.

To get a full glimpse into what AI companies have content marketing use cases, read the full blog post on the Marketing AI Institute here. 

What Do You Do Next?

It’s absolutely critical that content marketers go from theory to practice as fast as possible if they want to develop a competitive advantage with AI—and avoid getting left behind.

If you choose to take action, I hope you’ll join us in Cleveland, Ohio, July 16 - 18, 2019 for the inaugural Marketing Artificial Intelligence Conference (MAICON).

MAICON brings together top authors, entrepreneurs, AI researchers and executives to share case studies, strategies, and technologies that make AI approachable and actionable for marketers and salespeople.

In addition to relevant speakers and main tracks, the event also has a dedicated workshop for content marketing professionals, and 40+ sessions covering topics such as: advertising, analytics, content marketing, email marketing, ethics, robotics, sales, strategy, voice and more.