Using AI in content marketing is one of the top ways to increase revenue and/or reduce costs.
This isn't just speculation. Over 200 marketers told us this outright when they took our AI Score assessment.
In it, these professionals were asked to rate the value of using AI for 60+ marketing use cases. Out of the 10 highest-rated responses, seven were related to content marketing.
Turns out, marketers want to use AI to solve some of the common challenges we all face when trying to produce great content at scale, including:
- The need to analyze existing online content for gaps and opportunities.
- Keyword and topic cluster selection.
- Creating data-driven content, like reports and surveys.
- Getting insights into our top-performing content and campaigns.
- Optimizing content for search engines.
- Recommending targeted content to users in real-time.
- Assess and evolve creative (e.g. landing pages, email, CTAs) with A/B testing.
This isn't just wishful thinking, either.
We're seeing more and more marketers deploy AI tools to dramatically improve how fast and well they create and promote content. We're even using them on our own media properties, including this blog, to accelerate content success.
For instance, you may see a window pop-up on some of our blog posts labeled "Marketing AI Assistant." This is an AI-powered answer engine that uses our own website content to answer user questions. Over time, the answer engine improves the quality of its answers.
Behind the scenes, we're able to monitor common questions, then answer them on our blog as part of our content strategy.
Marketing AI Institute's AI-powered answer engine, courtesy of Frase.io.
As another example, we have started to use an AI-powered content strategy engine to identify what content to write next.
The tool helps us better understand what topic areas to focus on, and what subjects to cover in each post so we outrank the competition.
The tool doesn't drive our entire strategy. We still write plenty of fact-finding and thought leadership content in the form of expert spotlights, vendor interviews, and editorials like this one. But, AI augments our team by helping us produce search-friendly content at scale.
AI-powered content strategy, courtesy of MarketMuse.
Concrete examples like these are helpful.
But you also need to understand what AI is, if you want to use it for your own content marketing needs.
The good news?
You do not need to have a computer science, programming or data science background to understand AI for content marketing and begin applying it to your business.
You do, however, need a simple, actionable way to understand and approach AI, tailored for the challenges and opportunities in content marketing organizations.
This post is here to help.
What Is AI?
Ask 10 different experts what AI is, and you'll likely get 10 different responses of varying complexity.
Artificial intelligence is really an umbrella term for a suite of technologies (including machine learning, deep learning, and natural language generation), so the definition is open to interpretation.
We like a very simple definition from Demis Hassabis, the founder of an AI company called DeepMind. (DeepMind was acquired by Google in 2014.)
Hassabis says that AI is the "science of making machines smart." By that, he means we can teach machines to be human-like.
We can give machines the ability to see, hear, speak, move, and write. In all these cases, machines have a limited capacity to "understand" what these senses tell them.
As one example, think of photo tagging in Facebook. Facebook uses AI to see faces in photos, then "understand" who's in them.
Your home voice assistant hears what you say, "understands" what you're asking, and speaks an answer.
The autopilot function on a Tesla sees the world around it, "understands" where the obstacles are, and moves around them.
Predictive text in Gmail processes what you write, "understands" what you're trying to say, and writes what it thinks should come next.
In all of the above examples, the word understand is in quotes for a reason. The machines aren't actually understanding anything the way a human would. But they are predicting what comes next by assessing historical data at blinding speed, so that the best systems are able to see, hear, speak, move, and write in real-time.
At their core, AI-powered tools are prediction machines. This is what differentiates AI from traditional machines.
Traditional machines use algorithms to perform tasks. Algorithms are, simply, sets of instructions that tell machines what to do.
Think about your favorite marketing automation software. It is coded with rules, either by the company that built it or by you, the marketer, setting up workflows. The machine follows the instructions given to it. It can never deviate from those instructions or improve over time unless it is manually coded to do so.
With AI, however, the machine has the ability to create its own pathways using the algorithms it's given, sometimes without human intervention.
It gets smarter over time.
Don't worry, this doesn't mean we're talking about machines making their own decisions and taking over the world. It just means that AI technologies can sometimes optimize themselves to achieve certain goals without being explicitly coded that way by humans.
Here's a down-to-Earth example...
In the case of Gmail's predictive text feature, the tool predicts what you'll say next and begins to type it. It's often correct. And, it gets better over time because it's learning every time you accept or reject its suggested text. There isn't a programmer sitting in front of a server somewhere telling the tool what to do. The tool is using a set of algorithms to dynamically learn as it goes.
AI's ability to steadily improve over time means it can make astonishing leaps in power very quickly.
Gmail's predictive text feature began as a simple suggested response feature in the Gmail app. Instead of predicting as you type, it just suggested a few possible pre-written responses like "Thanks!" From that data, Gmail's AI technology was able to evolve to actually predict what you are writing in real time.
This type of AI-powered technology is now evolving into tools like GPT-2, an AI model capable of generating longform text (think: blog posts) without human involvement. This technological progression has happened in a span of just a few years.
And it is still early days. AI tools aren't replacing content marketers anytime soon. But they are transforming what is possible when you marry marketers and machines.
So, you don't need to fully understand all the ins and outs of AI to understand a few important points about the technology:
- AI is about making machines smart by teaching them to see, hear, speak, move, and write.
- AI is different from traditional technology because it can get smarter on its own.
- AI's ability to get smarter on its own means there is potential for AI-powered tools to improve very fast, unlocking new capabilities for marketers.
For content marketers, you really want to consider how all the tasks you do — or would like to do — in your organization fall into the categories of seeing, hearing, speaking, moving, or writing.
Those tasks are the first ones to explore when considering how AI can help your organization.
How to Get Started with AI for Content Marketing
But there's a long way to go from understanding AI to actually using it effectively. Without expert guidance, it's very easy to fail to implement AI or waste lots of time and money figuring it out.
This is why we created AI Academy for Marketers.
AI Academy for Marketers is an online education platform that brings the power of artificial intelligence to you.
The Academy is designed for manager-level and above marketers, and largely caters to non-technical audiences, meaning registrants do not need backgrounds in analytics, data science or programming to understand and apply what they learn.
The Academy features deep-dive Certification Courses (3 - 5 hours each), along with dozens of Short Courses (30 - 60 minutes each) taught by leading AI and marketing experts. There are 25+ Courses, including at least five Certificates, all available on-demand. The content is structured by marketing categories, and we plan to offer recommended Learning Paths as well for specific industries and job roles.
New content will be regularly added to the platform, and all Members get access to an exclusive online community to foster collaboration and knowledge sharing with their peers.
One of the Certification Courses is AI for Content Marketing 101, which teaches you exactly how to start using AI in your content programs.
The result? A potentially insurmountable advantage over competitors still creating content campaigns in a completely manual fashion.
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. An avid writer, Mike has published hundreds of articles on how to use AI in marketing to increase revenue and reduce costs. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). He is also the author of Bitcoin in Plain English, a beginner’s guide to the world’s most popular cryptocurrency.