Has artificial intelligence impacted storytelling? Not as much as you might think

Our obsession with technology has not only shaped the way we share ideas; it has fuelled our need to deliver information faster, on a broader scale, and with more impact. And in many ways, tools such as artificial intelligence (AI) and content automation software are changing how we tell stories.

For marketers, this is partly because AI helps to streamline time-consuming tasks such as collecting and analyzing data, which are critical for identifying content opportunities and measuring the success of past work. Personalization and segmentation are also made easier by AI and machine learning technology.

Tools like natural language generation take this even further, helping to craft messaging for specific audiences so that marketers can scale their content efforts. Choosing the perfect turn of phrase was supposed to be a subjective, creative process—but modern programmers are constantly exposing and simplifying the science behind it.

However, this has its limits. Today’s technology is useful in helping us tell stories that are not only informative, but data-informed—just look at how we use SEO to determine what stories to tell and how to message them. But looking further into the future, it’s pretty unlikely that we’ll be automating the full content marketing process anytime soon. And that’s probably for the best.

The need for creativity

The problem with AI and related tools is that in order to automate communications, they are constantly conforming to what has been said and done before. This might be useful in telling us what keywords are being searched this month in a particular industry—but it’s contradictory to taking a novel stance, articulating a unique perspective, or delivering any sort of interesting, differentiated value.

You probably encounter AI’s consensus-seeking tendencies every day thanks to simple autosuggest software—whether you’re typing in Google and a line of grey words suddenly tries to complete your thought for you, or your smartphone attempts to guess the next word you’re going to text based on what you’ve typed before.

Noted journalist, activist, and author Cory Doctorow points out that all “algorithmic inference” is permeated by this. Brands continue to advertise your latest purchase back at you, blindly basing it on your buying history, while YouTube believes you’ll like a video simply because it’s similar to one you viewed before.

So how does this relate back to content marketing automation and storytelling? Imagine you adopt the same content automation software as several other brands; if you’re all drawing from the same datasets, you’ll all be surfacing the same insights around what topics to cover, what platforms and channels to publish on, and what formats or structures to follow. Where does this lead? Content is homogeneous, you’re not delivering anything of value, and your voice is lost in the crowd.

That doesn’t mean you should avoid AI and automation. It simply means that when machines return results, it’s up to the smart people on your team to use their contextual knowledge, judgment, and critical thinking skills to synthesize the information and come up with insights that are unique, and meaningful to your audience.

James Gin, chief scientist at Datasine, explains that AI can make recommendations, but marketers are still needed to connect the dots. That’s because most AI operates as a “black box,” meaning that its decision making processes are opaque—and generally speaking, the more sophisticated the AI, the more opaque the black box.

This leads to problems that are not just practical, but ethical; and while Gin and his team have been training their own platform to use conversational descriptions to explain recommendations in a way that a human can understand, creative teams are still going to need to look critically at those suggestions.

The search for authenticity

Customers hold a great appreciation for brands that are genuine, and that interact with them in a way that’s individual and personalized, not programmatic or contrived. Yet companies are turning to tools such as chatbots and marketing automation for more of their customer touchpoints.

That doesn’t necessarily mean that they’re sacrificing their humanness. For instance, marketing automation allows companies to personalize messages, so that customers feel like they’re on a first-name basis with their favorite brands. Data analytics helps deliver the right messages to the right consumers at the right times.

Meanwhile, chatbots may not always sound or act like people, but by providing streamlined service, they respect customers’ time and address real needs—just look at the Incentive Assist chatbot PwC rolled out to instantly connect people with support programs in the midst of the COVID-19 pandemic. And besides just being all-around helpful, chatbots and automated assistants are becoming better conversationalists all the time—it’s almost creepy.

But all of this simply reaffirms what marketers already know: that all brands want to represent themselves as helpful and relatable on a human level, even as they rely on machines to engage; and customers follow, support, and champion brands not just because of the products and services they provide, but because of their likability, ethos, and character.

In short, what brands truly want is to be authentic, and authenticity is expressed through how a brand speaks—its voice and tone. By maintaining a voice that’s authentic to your company and values, and adjusting your tone to authentically suit your current context, you can tell an impactful story. But this demands a level of nuance that machines just can’t wrap their digital heads around.

The pursuit of purpose

Beyond simply sounding good, the best brand storytellers are actually doing good—and they leverage that so their customers know they’re not just buying into a product, but a purpose. Paul J. Zak, founding director of the Center for Neuroeconomics Studies, notes that it’s this transcendent purpose that motivates customers. In short, people care about the why much more than the what.

Most companies know this—yet many still struggle to tell stories that are meaningful, and others seem intent on finding more opportunities for machines to take over their customer interactions. All the while, they tell their marketing teams and partners that they want to sound more human and authentic. But you can’t always have it both ways. Ultimately, only humans are human, so use your talent.

In fact, it’s worth remembering that we humans are physically hardwired to share and value stories—hence that viewing, hearing, or reading a compelling narrative actually triggers the release of oxytocin, the so-called “love hormone” that leads to social bonding.

And for those narratives that aren’t compelling—too bad. Consumers may encounter up to 10,000 brand messages each day, which means they’ve become experts at tuning out the content that doesn’t make an impact. That’s why companies need to go to greater lengths to be genuine—not generic. As bestselling author Harrison Monarth notes, memorable stories and important messages get through to customers, not quantitative analysis and data.

But those aforementioned quantitative analyses and data do help inform which stories to tell—along with why, when, where, and to whom. And that’s where brands can bring AI and automation back into the picture.

The more things change, the more they stay the same

As digital technology plays an increasingly critical part in the daily lives of customers and the brands they interact with, it’s probably not a coincidence that “sounding human” has become marketers’ main objective, and “authenticity” is the attribute many customers count on to build trust.

Machines are helpful, but we can only take so much of them before we start to miss—and truly value—the sensitivity, spontaneity, intuitiveness, and individuality of a human voice telling a human story.

Image: pogonici/Shutterstock

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