When you think about artificial intelligence (AI), robots, androids and other futuristic technologies may come to mind. And while some of the most successful tech companies like Facebook, Amazon and Google have built their success on industry-changing applications of artificial intelligence, the concept is still fairly new to content marketing teams.

In the most basic sense “artificial intelligence” broadly refers to the processes and technologies that are created to teach machines to perform intelligent tasks. For content marketers, “intelligent tasks” typically refer to algorithms designed to process data. This goes far beyond automation, which is where the majority of marketing technology supports marketing teams today. Instead, AI gives marketing teams the ability to process big data extremely fast and then automatically identify patterns in the data to develop content and strategies better, faster and cheaper.

A familiar use case for many of us is how Netflix uses AI to suggest content and manufacture shows based on subscriber viewing habits and preferences. According to The Netflix Tech Blog, 75% of what people watch on Netflix is from an algorithm-generated recommendation.

We’re seeing similar applications with AI-based content marketing technologies, but the concept of machine-based marketing activities is still very new and oftentimes vague to even some of the most established marketing teams. While “AI” might seem like a buzzword, the smartest organizations are paying attention to how this technology can dramatically enhance the content marketing function.

If you’re eager to learn more about AI, machine learning and how intelligent technology is impacting content marketing, below is a brief FAQ with some top questions we get on the topic along with links to some must-read resources for a deeper dive into artificial intelligence.

What’s the difference between AI and machine learning?
Artificial intelligence is a broad field that covers many different applications and technologies, including machine learning, deep learning and natural language processing. Machine learning is just one type of AI that provides computers with the ability to learn without having to be programmed. Essentially, machine learning gives computers the ability to apply specific algorithms so they can teach themselves how to process new data.

How are machine learning and AI being used by content marketers today?
With the vast amount of AI-based technologies out there, the opportunity for AI and content marketing is tremendous. But one of the biggest opportunity areas we see today and the near future is with content personalization. This is something marketers have struggled with for a while now—getting the right content in front of the right person at the right time and doing it in the most efficient way possible.

Marketing technology using machine-learning algorithms can help brand publishers personalize their content based on user behavior and characteristics. These algorithms leverage big data, or large datasets consisting of rich information about a user’s content preferences, to target users with the right content consistently over time.

While many marketing personalization solutions take a more segment-based or rules-based approach, machine learning-based technology can predictively personalize content based on user behavior and context, delivering personalized experiences that are individually relevant to each person.

Another interesting AI use case primarily seen within the publishing sphere but closely related to content marketing is machine-based content generation. Publishers like the LA Times, Forbes and Associated Press use various language processing tools to produce fact-based articles, summaries and reports. These automated, algorithm-generated content primarily consist of data points and compilations of simple facts.

How will AI and machine learning impact the content marketing field?
One of the biggest burning questions for content marketers is this: will AI technology steal my job? The short answer is probably not. Instead, AI has the capability to dramatically enhance content marketing roles. AI takes traditionally human-powered and automated tasks and adds a cognitive layer to it (like natural language processing or machine learning), which allows algorithms to process large amounts of data. Machines can take on the more time-consuming tasks like keyword research, personalizing content and analyzing data, allowing content marketing teams to increase throughput and amplify what they’re able to do on a daily basis. Content marketers can focus on enhancing and optimizing content strategies, rather than creating everything from scratch.

“Cognitive technology is there to extend and amplify human expertise, not replace it.” —Rob High, Chief Technology Officer, IBM Watson

For example, Quill is an AI-based platform that uses natural language processing to take large amounts of intricate data sets and develop digestible content consisting of only the most important insights. Instead of manually analyzing, interpreting and communicating data, the platform does it automatically, freeing up employees to focus on other higher-value projects.

To further investigate the possibility of bots taking over the workplace completely, Oxford University analyzed over 700 jobs. “Writer/author” was relatively low on the list at 525. While AI can plow through mountains of data extremely fast, humans are still a critical component to the content creation process.

“We’re still a way off being able to give a computer a blank sheet of paper and telling them to come up with something,” says Future Content’s Stuart Roberts. “[Bots] will compile relevant information and present it in relevant ways, allowing the writer to come in, analyze the automated bot report and add insight, context and flair to the piece.”

Ready to see AI and machine learning in action? Get a demo of how OneSpot’s platform uses AI and machine learning to personalize content marketing across digital channels.