The Associated Press entered the realm of artificial intelligence in 2014, when it began to use an AI platform to write earnings reports. It was controversial at the time, but harnessing AI allowed the AP to increase the number of such reports that it published with less labor.
Now AI is an even bigger part of journalism and content marketing, with many outlets using the power of what The New York Times dubbed “robot reporters.” Bloomberg and The Washington Post use algorithms to write some stories, and the Times uses AI to customize its newsletters.
AI is also playing an increasing role for marketers, including content marketers. We use apps to check our grammar, we connect clients to customers with chatbots, and we rely on algorithms on LinkedIn, Facebook and Twitter to get our content in front of the right audiences.
However, there are still quite a few misconceptions surrounding the role of AI in content marketing. I spoke to a few pioneers in the field about what we should expect from AI in the future, and how content marketers can embrace these tools.
Defining AI in Content Marketing
Any discussion of AI has to begin with one of the most misunderstood things about it: What exactly does “artificial intelligence” mean?
One of the simplest definitions comes from the Marketing Artificial Intelligence Institute:
Artificial intelligence is the “science of making machines smart,” says Demis Hassabis, founder and CEO of AI company DeepMind. ... At a basic level, “smart” means achieving a goal by mimicking human cognitive functions. That goal could be winning a board game, correctly identifying a cat in a photo, adeptly using data from sensors to drive a car or anything else a human can do.
AI is simply the concept that machines can learn from prior experiences. It doesn’t mean machines will replace our ability to make decisions; for now, it’s just making them better at completing rote, repetitive tasks. How well they learn is determined by the humans who program them to find patterns within data.
It’s already a part of our lives: Tools like Apple’s Siri, the auto-complete functions on your smartphone and word processing tools, and products like Grammarly all rely on AI, as do the algorithms marketers rely on to distribute their content on social.
Upending Old Business Models — and Creating New Ones
One powerful example of AI in content marketing is Lonely Planet’s acquisition of AI company Trill. Trill leveraged AI to create bookable experiences through influencers’ content, turning photographs and their accompanying geotags into monetizable content. The acquisition is expected to extend this monetization capability. “I think the amount of information we’re able to pull automatically from a piece of content right now is just mind-blowing,” says Eric Shepard, a co-founder of Trill who is now a vice president of Lonely Planet Ventures.
This is just one example of how AI will become a larger part of the marketing landscape. AI tools can also help you craft your content strategy, including the best time to post a piece of content and which keywords you should target. “Things that every editor does are done exclusively manually right now. And none of it should be. Every one of those can be assisted by a machine,” says Paul Roetzer, founder of the Marketing Artificial Intelligence Institute.
Another example: The newsletter service rasa.io, which uses AI to create personalized content for newsletters. “With AI, what you’re able to do now is create your own great content — but acknowledge the fact that you are not the only place that people are going to for content,” says Jared Loftus, the company’s chief revenue officer. AI provides the ability to analyze the clicks people are attracted to, giving marketers more of the information they need to better serve the customer, he says.
Paul says AI’s most powerful feature is scalability. “AI simply has one capability that humans do not have: the ability to process data at a speed that seems near-instantaneous to our minds,” he says.
A Patient Approach to Implementing AI in Content Marketing
For those hoping to implement AI solutions, the first step is patience. Figuring out which tools your team needs is time-consuming, and educating yourself and your team is key, Paul says. The entire organization has to buy in, from management to those who will work with the tools daily.
The field is complex — and confusing, with many products trying to cash in on using the term “artificial intelligence” without providing much benefit. “Just because they say it in their branding doesn't necessarily mean that their product is actually any better than what you're already doing,” Paul says. Knowing your facts and speaking with peers are essential to making informed buying decisions. “It takes a little bit more education to be able to ask the right questions,” Paul says.
Eric says it’s important to start small. “He recommends targeting a specific solution that you believe a tool can help you achieve — perhaps a process that’s easily repeatable — and using it as a pilot program. This can provide you with a knowledge base and experience to embrace larger solutions.
But regardless of your enthusiasm around artificial intelligence, be prepared to encounter resistance. Many in your organization will think that AI will lead to job loss. Instead, turn once again to the power of education. Demonstrate how AI will make people’s lives easier and how it will free them to focus more on high-value, creative tasks. “In the content world, your imagination, your curiosity and your creativity are not being farmed out to AI,” Jared says. “It is a machine making better predictions.”
Wielding Power Wisely
As with any new technology, AI comes with caveats. Media reports have highlighted the power as well as the shortcomings of AI. “Sometimes AI gets colored as this magical, all-knowing thing that's going to fix all the problems that we've had,” Jared says. “It can amplify the problems we have if you don’t go about it correctly.”
One key issue is self-reinforcement. As an algorithm gets smarter, the chances of it revealing something surprising will diminish. “Sometimes you have to override data to tell an aspirational brand's story because the data speaks to your actual customers and not your aspirational customers,” says Brad Simms, president and CEO at GALE. Brad’s advice is a reminder that human beings are the ultimate power behind artificial intelligence, and that it can only learn what we program it to learn.
The efficacy of AI is determined by what you do with it — and what you choose not to do with it. Give those engaging with your content permission to set the parameters for the data they share with you, or to not share data at all. Welcome them to your content, rather than invading their inbox and privacy. This will build trust for the brands you represent.
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