Artificial intelligence (AI) is eating the world, one boring, routine task at a time.
From navigation apps using AI to crunch a bunch of data at a super-fast speed to determine the best and fastest route from A to B, or automatic spam filters and categorizations that make email more manageable, AI is truly ubiquitous.
It was only a matter of time before AI applications in the content management space arose. And when it comes to content ops, the combination of content management and artificial intelligence is a great tool for giving workers back the time they need to perform more complex tasks that still require a human brain.
AI excels at ‘understanding’ vast pools of data and automating routine tasks. This is typically orientated towards objectives of improving consumer experiences, saving the time and money invested in routine processes, and even exposing patterns that can uncover new revenue opportunities.
These are typically seen in a content operations workflow in four areas:
AI can analyze a piece of content to identify its sentiment and overall tone, very quickly. This is important for helping content managers determine whether a piece of content is right for their audience or if it needs tweaking before it will truly engage the intended consumer. IBM Watson, for example, uses AI to automate content categorization, text labeling, sentiment analysis, keyword extraction, and more.
A picture still tells a thousand words. Images enhance content increase engagement. Unfortunately, there is almost nothing less engaging for workers than manually tagging image after image for search and SEO purposes. But it is still a supremely important task. And that is what makes it a great job for AI.
AI-powered automated image recognition is now smart enough to tag images in a matter of seconds—letting content workers get back to deeper work instead of routine classification.
AI also brings scalability to another important but nearly impossible task for human staff: tracking and making use of individual user behavior.
AI can automate the process of watching what each user on a website or app is doing simultaneously. Then, it can compile this data to look for patterns that will help it predict, based on past behavior, what each user might want next.
This information can dramatically improve Personalization efforts, from serving dynamic content to making product recommendations and more. And improving Personalization has never been more important. In the words of the management consulting firm McKinsey, “Personalization will be the prime driver of marketing success within five years.” In fact, they found that leaders in personalization were already able to increase revenue by 5 to 15 percent and improve efficiency on marketing spend by 10 to 30 percent. Achieving that kind of improvement automatically is a massive competitive advantage.
Controversially, AI can also be a big help when it comes to creating content.
Whilst artificial intelligence still is not great at coming up with original ideas or creating nuanced pieces of content, it is catching up fast.
