No matter what content you write or what stories your brand tells, there’s a good chance artificial intelligence (AI) can help you do it better.
Despite the hype you hear, AI is a very real force in marketing. And it's changing the way brands create and distribute content.
At Marketing AI Institute, we've spent years researching and applying AI in marketing and sales.
And content marketing is one of the top areas we've seen marketers use AI to significantly increase revenue and reduce costs.
In fact, we surveyed hundreds of marketers for our 2021 State of Marketing AI Report, about how valuable it would be to use AI technology to intelligently automate more than 45 common AI use cases in marketing.
Content marketing activities dominated the list of highest-rated use cases for AI in marketing. These include content analysis, keyword selection, data-driven content creation, optimization, creating personalized content, and A/B testing to improve content.
All of these content marketing use cases — and many more — are possible to do with AI today.
What is AI? How do you get started? What use cases and tools should you investigate?
This post has you covered.
What is AI and how does it influence content marketing?
AI 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.
How can AI help content creation and content marketing?
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.
In 2020, OpenAI updated the model and released GPT-3.
In early experiments, GPT-3 has been used to produce everything from coherent blog posts to press releases to technical manuals, often with a high degree of accuracy. To do that, GPT-3 uses 175 billion parameters in its language model, compared to GPT-2's 1.5 billion.
The point here isn’t to say AI will replace writers or remove the need for content marketers, though that could happen if the technology progresses far enough and fast enough.
It’s to highlight that this is real technology that is making real progress towards doing certain marketing tasks better than humans.
That has forward-thinking marketers adopting the technology to increase revenues, reduce costs, and build massive competitive advantages.
What AI skills do content marketers need?
Let's start with what skills that may not be valuable moving forward in content marketing.
It's difficult to predict which exact roles and skills will be affected by AI and intelligent automation. However, the following types of skills are more susceptible to automation thanks to AI.
- Repetitive. Tasks that are completed following a set of repeatable steps that don't change much are susceptible to automation.
- Data-driven. Tasks that rely on data to produce outputs are often ripe for applying AI.
- Predictive. Tasks that require making a prediction about an outcome are tasks that AI excels at.
Tasks and roles that have one or more of the above characteristics are more likely than others to become partially or fully automated by AI.
But, what skills do content marketers need to develop in order to survive and thrive in the age of AI?
Broadly, there are a few skills content marketers need to start honing if they want to take advantage of AI in the coming months and years.
- AI knowledge and understanding. You don't need to know everything about AI to start using the technology. But you do need a basic understanding of the different types of AI technology, and the opportunities and challenges AI presents. Our Beginner's Guide to AI in Marketing is a great start to build this foundation fast.
- Data literacy. You also don't need a degree in data science to use AI to develop a competitive advantage. You do, however, need to understand basic data literacy and how data impacts AI adoption. Don't worry, you don't need to be a math whiz to do this. But you do need clear guidance on how to think about data and AI. This post summarizing our interview with expert data scientist Cal Al-Dhubaib is a good initial primer.
- Use cases. You also need to understand how AI can actually help your content marketing. That way, you can get ahead of the curve and begin testing tools. This post is a solid start. You can also use our free interactive AI Score for Marketers tool to rate your top AI use cases in content marketing and other areas quickly and easily—even if you're just getting your feet wet with AI.
What are some AI-powered marketing tools?
AI tools for content production
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.
MarketMuse is an AI-driven assistant for building content strategies. The tool will show you exactly what terms you need to target to compete in certain topic categories. It'll also surface topics you may need to target if you want to own certain topics.
The result? AI-powered SEO recommendations and insights that can guide your entire content creation team.
rasa.io is an AI platform that generates personalized, Smart Newsletters and automates the newsletter production process, dramatically increasing reader engagement, and providing rich insights back to the brand.
AI tools for content 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.
Crayon uses AI to give you competitive intelligence on exactly what your competitors are doing online. You’ll be able to see how the main pages of a company’s website change over time, which in turn reveals insights about their content strategy, targeting, and messaging.
Cobomba is an AI-powered content intelligence platform. It measures your content metrics over time, so you can track performance at scale. And it offers smart recommendations on how to improve content effectiveness.
AI tools for content optimization and recommendation
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:
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.
BrightEdge is a global leader in SEO and content performance marketing that blends search intent discovery, optimized content creation, and performance measurement into one integrated solution.
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.
PathFactory uses sophisticated AI to hyper-personalize the B2B buyer's journey. The company's content insight and activation platform helps buyers to move through their paths to purchase faster and more easily by serving them relevant content recommendations.
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). See Mike's full bio.