The term “artificial intelligence” simply means a computer system that mimics the thought processes of the human mind. The Turing test set the gold standard for AI systems in the 1960’s by asking whether or not a computer-generated conversation could fool a human audience. These days, it’s not so much about fooling audiences as it is about providing the most relevant, up-to-the minute content as possible. And since AI has proven highly useful in telling us what resonates with audiences, it’s entirely possible that very soon AI could also produce the kinds of content it predicts audiences want.
AI isn’t just revolutionizing content; it’s pretty much changing the way we see the world. In fact, Elon Musk recently predicted that computers will be indistinguishable, or even better than humans at “everything,” by 2030 at the earliest and 2060 at the latest. And it looks like Google agrees since, in 2017, the company sunk $800,000 into the Press Association’s plans to use AI in order to generate news stories.
And while computers that surpass us in every way seem more like the plot of a dystopian novel than something bound to happen before today’s toddlers graduate high school, AI is actually being used right now to generate everything from news stories to hyper-personalized emails.
In the past, the industry has been a bit short sighted about the possibilities for artificial intelligence. It’s commonly assumed, for example, that artificial intelligence is the solution to problems inherent in media buying, such as transparency and human biases often gumming up the process.
But the assumption that artificial intelligence is the solution to our media buying woes also often goes hand-in-hand with the idea that the whole point of allowing AI to cover the more analytic and data-centric parts of the content marketing process will free up more human time for the creative aspects of a campaign.
However, those ideas are quickly proving outdated as brands like H&M and Sephora have adopted AI into their retail strategies by using chatbots to improve their customer-service experience. The brands are now allowing bots to handle everything from scheduling store visits to answering customer’s commonly asked questions. And while the process is far from perfect, it’s a great example of how AI technology is not just passing, but surpassing, the Turing test.
And if AI can revolutionize retail, it also stands to reason that AI is all set to shake up content marketing.
Increasingly, we rely on AI technology to measure the success of keywords, headlines, images and stories, and those measurements have drastically altered the kinds of content we produce. For example, data analytics have made it common knowledge audiences are more likely to engage with text that includes images, so marketers have made an increased effort to assign images to posts.
But now, AI that not only tells us what content resonates with audiences but can also serve to generate that same content is changing the way many marketing innovators are engaging with audiences, and even the ways we think about what “good” writing is.
Case in point: as hard as it may be to imagine a robot that can write War and Peace, that very scenario might actually soon be the case. In 2016, a short work generated by an AI system was actually a finalist for a Japanese fiction contest, further proving that, when it comes to content creation, AI isn’t just a fairy tale.
Two years ago, Gartner predicted that by 2018, 20% of business content would be computer-generated. The jury’s still out on whether that prediction came true, but judging by how successfully many organizations have integrated AI content creation into their storytelling strategies, the number could be spot on.
Here are just a few examples:
If you’ve checked the scores for your favorite teams any time in the past three years, you’ve probably read computer-generated content.
In 2016, The Washington Post launched Heliograph, an AI content generator, to help with its coverage of the 2016 Olympics in Rio. Since then, the system has revolutionized the way the newspaper creates content, allowing for the quick generation of hyperlocal stories based on “scoring plays, individual player statistics and quarterly score changes, along with The Post’s own weekly Top 20 regional rankings.” The result is hundreds of highly relevant news stories the newspaper couldn’t have dreamed of having the manpower to cover.
The Los Angeles Times is taking the same AI content generation technology that helped The Washington post revolutionize sports reporting to help keep citizens safe from earthquakes. EQBOT uses data about earthquakes around metropolitan areas from the U.S. Geographical Survey to write news stories warning readers. The bot is even responsible for its own Twitter account.
Disney has long been an icon of American storytelling, and now the company might soon rely on AI to dream up and execute their next blockbuster. Based on data around upvotes and downvotes from the Q + A site Quora, Disney is working on AI that will mimic the human brain in determining what makes a story compelling and then tells those stories in a way that resonates with audiences.
Recently the Florida-based basketball team used Wordsmith to help make its emails hyper-personal. The Magic’s marketing team relies on SAS (statistical analysis system) technology to let them know not only which season ticket holders have posted their tickets for resale online, but also which of those ticket holders are the least likely to be able to resell their tickets online. Then a content generator delivers a personalized email reminding ticket-holders that they can resell their tickets to the team for “Magic Money.” The AI-driven personalized emails have been highly effective, earning an 80% positive email response and a significant boost in awareness around its loyalty program.
AI content marketing could mean huge changes in the ways that B2B companies communicate with their audiences.
Ironically, as customers demand greater personalization from marketing, human marketers are finding it more difficult to keep up. Accenture recently reported that 56% of people are more likely to buy after being addressed by name, and McKinsey & Company found that personalization can deliver eight times the ROI on marketing spend. Yet 83% of marketers struggle with personalization.
The solution might just lie in AI. Not only can AI systems analyze clicks, open rates, and even social media, programs can also generate content based on those triggers that not only addresses audience by name, but also gives them relevant information in an appealing tone. Imagine how much easier it would be to talk to audiences in their own language rather than drafting, editing, and revising a tone that appeals to everyone.
Of course, AI-generated content marketing is still in its infancy, as evidenced by ClickZ’s own attempt to use a content creation product called Articoolo to produce one of its news stories. The result is an awkward, but serviceable article that gave all the facts with none of the finesse a human writer might add. Still there was “nothing there that a human editor couldn’t fix quickly enough,” according to ClickZ reporter Mike O’Brien.
Perhaps the biggest fear around AI is the worry that computers are coming to take all our jobs. A recent Gallup study found that 73% of Americans were pretty sure that humanistic robots will eliminate more jobs than they generate, yet a scant 23% of respondents were worried about AI taking their jobs.
Should content marketers be worried about losing their gigs to robots? Probably not. Computers are still unable to empathize and have a real difficulty reflecting human emotions, so it’s all but impossible for them to create stories that are truly personal, which is why The New York Times isn’t in a rush to outsource its Modern Love column to a tearjerker generator just yet.
However, considering the possibilities of AI for content marketing makes sense for marketers looking at new ways to efficiently create personalized content. Audiences want storytelling that resonates with who they are, and the same technology that allows us to pick up data clues for personalization could also help us to tell stories that resonate with customers on an individual level.
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